automated glacier segmentation by fast adaptive medoid shift algorithm



Anastasios Kouvelas Adaptive Fine-tuning for Large-scale Nonlinear Control Systems Anastasios Kouvelas Adaptive Fine-tuning for Large-scale Nonlinear Control Systems Новинка

Anastasios Kouvelas Adaptive Fine-tuning for Large-scale Nonlinear Control Systems

4983 руб.
Despite the continuous advances in the fields of control and computing, the design and deployment of an efficient Large-scale Nonlinear Traffic Control System (LNTCS) remains a significant objective. This is mainly due to the complexity and strong nonlinearities involved in the modeling of traffic flow processes. The ultimate performance of a designed or operational LNTCS depends on two main factors: (a) the exogenous influences, and (b) the values of some design parameters included within the LNTCS. When a new control algorithm is implemented there is a period of, sometimes tedious, fine-tuning activity that is needed in order to elevate the control algorithm to its best achievable performance. Fine-tuning concerns the selection of appropriate values for a number of design parameters included in the control strategy. This thesis introduces and analyzes a new learning/adaptive algorithm that enables automatic fine-tuning of LNTCS, so as to reach the maximum performance that is achievable with the utilized control strategy. The proposed Adaptive Fine Tuning (AFT) algorithm is aiming at replacing the conventional manual optimization practice with a fully automated online procedure.
Adebimpe Azeez Ayodeji Influence of Brain MRI Segmentation Techniques on Eeg Source Analysis Adebimpe Azeez Ayodeji Influence of Brain MRI Segmentation Techniques on Eeg Source Analysis Новинка

Adebimpe Azeez Ayodeji Influence of Brain MRI Segmentation Techniques on Eeg Source Analysis

6314 руб.
This study investigates influence of brain MR segmentation techniques and implements a framework in Python for a uniform interface to the three different automated segmentation software tools (SPM,FSL and FreeSurfer) in order to be able to compare them consistently. This is done by using the Nipype (Neuroimaging in Python, Pipelines and Interfaces) which provides a uniform interface to these neuroimaging software tools. In addition, the tissue probability maps, masks and surfaces that are required for the head model construction are generated with this framework. The source reconstruction results with the head models constructed with different segmentation tools are evaluated based on the distance error from the source location to the lesion in the post-operative MR images. The SPM head models produced lowest distances error compared to the FSL and the FreeSurfer head models for two patients.
Arjun Nelikanti Colorectal Cancer MRI Image Segmentation Using Image Processing Techniques Arjun Nelikanti Colorectal Cancer MRI Image Segmentation Using Image Processing Techniques Новинка

Arjun Nelikanti Colorectal Cancer MRI Image Segmentation Using Image Processing Techniques

1977 руб.
Master's Thesis from the year 2014 in the subject Medicine - Biomedical Engineering, grade: 76, , course: Image processing, language: English, abstract: Colorectal cancer is the third most commonly diagnosed cancer and the second leading cause of cancer death in men and women. Magnetic resonance imaging (MRI) established itself as the primary method for detection and staging in patients with colorectal cancer. MRI images of Colorectal cancer are used to detect the area and mean values of tumor area and distance from tumor area to other parts. The thesis describes algorithms for preprocessing, clustering and post processing of MRI images. Implemented algorithm for preprocessing using image enhancement techniques, clustering is done using adaptive k-means algorithm and post processing using image processing techniques in MATLAB.
Simon Haykin Kernel Adaptive Filtering. A Comprehensive Introduction Simon Haykin Kernel Adaptive Filtering. A Comprehensive Introduction Новинка

Simon Haykin Kernel Adaptive Filtering. A Comprehensive Introduction

9451.22 руб.
Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm Presents a powerful model-selection method called maximum marginal likelihood Addresses the principal bottleneck of kernel adaptive filters—their growing structure Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site Concludes each chapter with a summary of the state of the art and potential future directions for original research Kernel Adaptive Filtering is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.
Abid Shahid Segmentation of Cursive Textual Images (Applied to Urdu Script) Abid Shahid Segmentation of Cursive Textual Images (Applied to Urdu Script) Новинка

Abid Shahid Segmentation of Cursive Textual Images (Applied to Urdu Script)

9527 руб.
Segmentation of Cursive Textual Images (Applied to Urdu Script) is designed for students perusing the subject at both undergraduate and postgraduate levels. Features: • Enable students to see how algorithms like artificial neural network (ANN), hidden Markov Model (HMMs) etc. work. • Enable them to understand images, various operations on images and algorithms. • Explain the various implementations of HMMs on values and images. • Includes step-by-step instructions to apply algorithms to solve multi-dimensional problems. • It explains textual images (using Urdu script as example), its cursive nature and difficulties for a computer program to identify characters in textual image. • It also explains glyph or connected component analysis. • It explains ANN algorithm and how it can solve segmentation/recognition of holistic images. • It explains how HMMs is used for the segmentation of Urdu text at character level. • It also explains the mathematical equations involved in HMMs. • It also discussed the limitations of algorithm using bounding box, ANN and HMMs. • Includes comprehensive appendix and important tables, graphs and mathematical equations.
Nawaz Aamir Nelder Mead Trained Neural Networks For Short Term Load Forecasting Nawaz Aamir Nelder Mead Trained Neural Networks For Short Term Load Forecasting Новинка

Nawaz Aamir Nelder Mead Trained Neural Networks For Short Term Load Forecasting

7277 руб.
This book proposes a new optimization algorithm for solving short term load forecasting problem. Globalized Nelder Mead is used for training of Artificial Neural Networks. Nelder Mead is fast optimization algorithm with no gradient calculation. The weights of Neural Networks are tuned with the help of Nelder Mead algorithm. To find proficiency of this algorithm, Australian Energy Market Operator (AEMO) data and California data are taken for testing. Results show that proposed algorithm outclasses other techniques in literature.
Anastasia Paparrizou Efficient Algorithms for Strong Local Consistencies and Adaptive Techniques in Constraint Satisfaction Problems Anastasia Paparrizou Efficient Algorithms for Strong Local Consistencies and Adaptive Techniques in Constraint Satisfaction Problems Новинка

Anastasia Paparrizou Efficient Algorithms for Strong Local Consistencies and Adaptive Techniques in Constraint Satisfaction Problems

1489 руб.
Constraint programming is a successful technology for solving a wide range of problems in business and industry which require satisfying a set of constraints. Central to solving constraint satisfaction problems is enforcing a level of local consistency. In this thesis, we propose efficient filtering algorithms for enforcing strong local consistencies. In addition, since such filtering algorithms can be too expensive to enforce all the time, we propose some automated heuristics that can dynamically select the most appropriate filtering algorithm. Published by AI Access, a not-for-profit publisher of open access texts with a highly respected scientific board. We publish monographsand collected works. Our texts are available electronically for free and in hard copy at close to cost.
Lina Gundelwein 3D segmentation and boundary completion using subjective surface method Lina Gundelwein 3D segmentation and boundary completion using subjective surface method Новинка

Lina Gundelwein 3D segmentation and boundary completion using subjective surface method

1852 руб.
Bachelor Thesis from the year 2015 in the subject Mathematics - Applied Mathematics, grade: 1,0, Friedrich-Alexander University Erlangen-Nuremberg (Angewandte Mathematik III), language: English, abstract: Segmentation is used to locate boundaries of an object in a given image. Finding those boundaries is important e.g. for visualizing three dimensional objects and measuring their surface or volume. Ideally, the boundaries coincide with the edges seen in the image. However, due to noise, partly missing information or in case of subjective contours the edges can be irregular and discontinuous. The human brain is able to perform visual completion that is to say it can in many cases complete those interrupted boundaries by filling in the missing gaps. Simple segmentation methods fail to do so, whereas the subjective surface method succeeds by sharpening the surface around the edges and connecting segmented boundaries across the gaps. Michael Fried is using finite elements with the subjective surface method resulting in an algorithm that detects interrupted boundaries as well as subjective contours in 2D. As an extension of Michael Fried's work, the algorithm presented in this thesis is able to complete missing boundary segments in 3D, smooth out the contours and perform modal completion.
Supaporn Lamnoi Student Modeling and Adaptive Hypermedia for E-learning Systems Supaporn Lamnoi Student Modeling and Adaptive Hypermedia for E-learning Systems Новинка

Supaporn Lamnoi Student Modeling and Adaptive Hypermedia for E-learning Systems

8789 руб.
This book is very useful to create an adaptive e-Learning system by using student modeling and adaptive hypermedia. Adaptive e-Learning is an enhancement to make e-Learning system more effective by adapting the presentation of information and overall link structure to each individual user based on her/his knowledge and behavior. The adaptive e-Learning system provides better flexibility and capability than non-adaptive e-Learning system. It also leads the students to better learning results. Certainly, the adaptive e-Learning systems will benefit students' academic performance.
Srivani Pinneli Predicting the Perceived Interest of Object in Images Srivani Pinneli Predicting the Perceived Interest of Object in Images Новинка

Srivani Pinneli Predicting the Perceived Interest of Object in Images

9464 руб.
This book presents an algorithm that uses a "Bayesian probabilistic apprroach" to compute the perceived interest of objects in images. A set of likelihood functions were measured via a psychophysical experiment in which subjects rated the perceived visual interest of over 1100 objects in 300 images. These results were then used to determine the likelihood of perceived interest given various factors such as location, contrast, color, luminance, edge-strength and blur. These likelihood functions are used as part of a Bayesian formulation in which perceived interest is inferred based on the factors mentioned above. Our results demonstrate that our algorithm can perform well in predicting perceived interest. A block-based approach is also proposed which doesn't need segmentation and is fast- enough to be used in real-time applications.
Ozgur Ergul The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large-Scale Computational Electromagnetics Problems Ozgur Ergul The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large-Scale Computational Electromagnetics Problems Новинка

Ozgur Ergul The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large-Scale Computational Electromagnetics Problems

15184.14 руб.
The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large-Scale Computational Electromagnetic Problems provides a detailed and instructional overview of implementing MLFMA. The book: Presents a comprehensive treatment of the MLFMA algorithm, including basic linear algebra concepts, recent developments on the parallel computation, and a number of application examples Covers solutions of electromagnetic problems involving dielectric objects and perfectly-conducting objects Discusses applications including scattering from airborne targets, scattering from red blood cells, radiation from antennas and arrays, metamaterials etc. Is written by authors who have more than 25 years experience on the development and implementation of MLFMA The book will be useful for post-graduate students, researchers, and academics, studying in the areas of computational electromagnetics, numerical analysis, and computer science, and who would like to implement and develop rigorous simulation environments based on MLFMA.
Nithya Venkatachalam, Vaiyshnavi Perumal Improved Scheduling Algorithm Using Dynamic Tree Construction for Wireless Sensor Networks Nithya Venkatachalam, Vaiyshnavi Perumal Improved Scheduling Algorithm Using Dynamic Tree Construction for Wireless Sensor Networks Новинка

Nithya Venkatachalam, Vaiyshnavi Perumal Improved Scheduling Algorithm Using Dynamic Tree Construction for Wireless Sensor Networks

5114 руб.
The Wireless Sensor Network (WSN) composed of several nodes is used for different types of monitoring applications. The objective of deploying WSN is to observe a particular site for monitoring physical parameters like temperature, light, pressure, humidity or the occurrence of a phenomenon. The Sleep/Wake up scheduling for Wireless Sensor Networks has become an essential part of its working.In this book, the details of Low Energy Adaptive Clustering Hierarchy (LEACH) which introduces the concept of clustering in sensor networks, Energy-Efficient Clustering routing algorithm based on Distance and Residual Energy for Wireless Sensor Networks (DECSA) which describes scheduling based on distance and energy, and the Energy efficient clustering algorithm for data aggregation (EECA) are discussed. The LECSA (Load and Energy Consumption based Scheduling Algorithm) are also discussed.
Aliyu Muhammad Lawan, Salman Mohammad Shukri Sparse Adaptive Filtering Techniques for Channel Estimation Aliyu Muhammad Lawan, Salman Mohammad Shukri Sparse Adaptive Filtering Techniques for Channel Estimation Новинка

Aliyu Muhammad Lawan, Salman Mohammad Shukri Sparse Adaptive Filtering Techniques for Channel Estimation

5214 руб.
Recently,sparse signal approximation has become an increasingly important research area in signal processing. It attracts a lot of interest due to its wide range of practical applications. In this work, a novel adaptive filtering algorithm with relative low computational complexity that is capable of exploiting the sparsity of systems is proposed. The basic idea here is, we adopt a p-norm constraint in the cost function of the variable step-size least mean square (VSSLMS) algorithm. This constrain imposes a zero attraction at each filter coefficient based on their respective relative value. Also, the convergence analysis of the proposed algorithm is presented and the stability condition is derived. The performance of the proposed algorithm has been compared to those of the Zero Attraction Least Mean Square(ZA-LMS), windowing ZA-LMS(wZA-LMS), Non-uniform Norm Constraint LMS(NNCLMS) in a system identification setting for different additive Gaussian noise(AGN), additive correlated noise(ACN)and additive impulsive noise(AIN) environments. The proposed algorithm has always shown superior performance to the others with less or comparable number of computations.
Автомобильное зар./устр. Samsung EP-LN930BBEGRU 2A+1.67A универсальное кабель microUSB черный Автомобильное зар./устр. Samsung EP-LN930BBEGRU 2A+1.67A универсальное кабель microUSB черный Новинка

Автомобильное зар./устр. Samsung EP-LN930BBEGRU 2A+1.67A универсальное кабель microUSB черный

1520 руб.
Автомобильное зарядное устройство для мобильных устройств microUSB с функцией быстрой зарядки (Adaptive Fast Charging).
Tsiptsis Konstantinos K. Data Mining Techniques in CRM. Inside Customer Segmentation Tsiptsis Konstantinos K. Data Mining Techniques in CRM. Inside Customer Segmentation Новинка

Tsiptsis Konstantinos K. Data Mining Techniques in CRM. Inside Customer Segmentation

7788.55 руб.
This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.
Rongfang Liu Automated Transit. Planning, Operation, and Applications Rongfang Liu Automated Transit. Planning, Operation, and Applications Новинка

Rongfang Liu Automated Transit. Planning, Operation, and Applications

7743.11 руб.
A comprehensive discussion of automated transit This book analyzes the successful implementations of automated transit in various international locations, such as Paris, Toronto, London, and Kuala Lumpur, and investigates the apparent lack of automated transit applications in the urban environment in the United States. The book begins with a brief definition of automated transit and its historical development. After a thorough description of the technical specifications, the author highlights a few applications from each sub-group of the automated transit spectrum. International case studies display various technologies and their applications, and identify vital factors that affect each system and performance evaluations of existing applications. The book then discusses the planning and operation of automated transit applications at both macro and micro levels. Finally, the book covers a number of less successful concepts, as well as the lessons learned, allowing readers to gain a comprehensive understanding of the topic. Key features: Provides a thorough examination of automated transit applications, their impact and implications for society Written by the committee chair for the Automated Transit Systems Transportation, Research Board Offers essential information on planning, costs, and applications of automated transit systems Covers driverless metros, automated LRT, group and personal rapid transit, a review of worldwide applications Includes capacity and safety guidelines, as well as vehicles, propulsion, and communication and control systems This book is essential reading for engineers, researchers, scientists, college or graduate students who work in transportation planning, engineering, operation and management fields.
Jason Brownlee Clever Algorithms. Nature-Inspired Programming Recipes Jason Brownlee Clever Algorithms. Nature-Inspired Programming Recipes Новинка

Jason Brownlee Clever Algorithms. Nature-Inspired Programming Recipes

4127 руб.
This book provides a handbook of algorithmic recipes from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence that have been described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described in this book were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.
Shady S. Al-Atrash, Ibrahim Abuhaiba Robust Face Recognition Shady S. Al-Atrash, Ibrahim Abuhaiba Robust Face Recognition Новинка

Shady S. Al-Atrash, Ibrahim Abuhaiba Robust Face Recognition

8102 руб.
The objective of this book is to propose a new algorithm for obtaining a stable face detection and recognition techniques that have the capabilities of detecting the face with different poses and under different conditions. To obtain this stability, a hybrid of Feature-Based and Template Matching approaches are used in a new manner and under different stages, robust image segmentation, filtering steps and features detection using Feature-Based approach which can work in real-time with minimal training in contrast to other approaches such as image-based approach. This work has advantages over other approaches flow out from the ability of the proposed algorithm on detecting faces with different poses (Left, Right and Frontal) in varying illumination conditions and different races. This is done by merging some already defined algorithms such as Template Matching with new proposed algorithm to strength the detection process and obtaining robust algorithm with good results. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses and different races.The proposed method gives a correct detection rate reach 94%.
Lemias Zivanai TDMA scheduling of Multimedia traffic in Multiple hop MANETS Lemias Zivanai TDMA scheduling of Multimedia traffic in Multiple hop MANETS Новинка

Lemias Zivanai TDMA scheduling of Multimedia traffic in Multiple hop MANETS

3212 руб.
The research presents a adaptive TDMA slot assignment algorithm, called MDRAND, which is a modified version of DRAND in clustered wireless sensor networks where cluster nodes need its own time to transmit and receive. Priorities will be given to traffic which is real time applications and best effort applications. It utilizes on the requests which will be send by nodes which would be willing to send. Reservation of slots will be done on upon requests. Simulation results show that time complexity and space complexity is (On) which is similar to that of DRAND algorithm.
Yahya Ali Abdelrahman Ali Similarity Measures Using Genetic Algorithm for Searching Chemical DB Yahya Ali Abdelrahman Ali Similarity Measures Using Genetic Algorithm for Searching Chemical DB Новинка

Yahya Ali Abdelrahman Ali Similarity Measures Using Genetic Algorithm for Searching Chemical DB

5224 руб.
Similarity searching is a process to find compounds that are similar to a target compound, which is useful in discovering potential drugs.this study is to optimize weights of different similarity measures in data fusion for searching chemical database by applying genetic algorithm (GA).Comparisons of different coefficient fusions were carried out.Using combination with weights ranging between 0.0 and 1.0 generated by genetic algorithm, gave a better number of active than the non-weighted combination.
The Algorithm (France) The Algorithm (France) Новинка

The Algorithm (France)

1500 руб.
Printio Shift gears... Printio Shift gears... Новинка

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1109 руб.
Майка классическая — цвет: ЧЁРНЫЙ, пол: ЖЕН. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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Printio Shift gears...

924 руб.
Детская футболка классическая унисекс — цвет: ЧЁРНЫЙ, пол: МУЖ. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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1190 руб.
Футболка Wearcraft Premium — цвет: ЧЁРНЫЙ, пол: ЖЕН. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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1453 руб.
Лонгслив — цвет: ЧЁРНЫЙ, пол: МУЖ. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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1109 руб.
Майка классическая — цвет: ЧЁРНЫЙ, пол: МУЖ. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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1370 руб.
Футболка Wearcraft Premium Slim Fit — цвет: ЧЁРНЫЙ, пол: МУЖ. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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1249 руб.
Футболка классическая — цвет: ЧЁРНЫЙ, пол: МУЖ, качество: ЭКОНОМ. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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1090 руб.
Футболка классическая — цвет: ЧЁРНЫЙ, пол: ЖЕН. Shift Gears & Burn Rubber t-shirt black Design by Shap.Design™
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2319 руб.
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Christo Ananth Fast Active Queue Management Stability Transmission Control Protocol (FAST TCP) Christo Ananth Fast Active Queue Management Stability Transmission Control Protocol (FAST TCP) Новинка

Christo Ananth Fast Active Queue Management Stability Transmission Control Protocol (FAST TCP)

5352 руб.
Project Report from the year 2017 in the subject Engineering - Computer Engineering, grade: 4.5, , language: English, abstract: In this project, we describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties, at both packet and flow levels, which the current TCP implementation has at large windows. We describe the architecture and characterize the equilibrium and stability properties of FAST TCP. We present experimental results comparing our first Linux prototype with TCP Reno, HSTCP, and STCP in terms of throughput, fairness, stability, and responsiveness. FAST TCP aims to rapidly stabilize high-speed long-latency networks into steady, efficient and fair operating points, in dynamic sharing environments, and the preliminary results are produced as output of our project. We also explain our project with the help of an existing real-time example as to explain why we go for the TCP download rather than FTP download. The real-time example that is chosen is Torrents which we use for Bulk and safe-downloading. We finally conclude with the results of our new congestion control algorithm aided with the graphs obtained during its simulation in NS2.
Haider Ali Digital Image Segmentation Variational Models Haider Ali Digital Image Segmentation Variational Models Новинка

Haider Ali Digital Image Segmentation Variational Models

3944 руб.
Image segmentation is a fundamental task in image processing and computer vision. Applications of image segmentation are urgent important, e.g. Robot Vision, Medical Imaging, Radar Imaging, Sonar Imaging, Remote Sensing, Astronomy, Traffic, Defense, Mining, Object Tracking and Detection, Finger Print Detection and so on. The main aim of image segmentation is to extract meaningful objects from a given image. For example, a boy of just three years can see/detect/locate a pen on a table, as he is naturally equipped with image segmentation power, robots can not do it, until they use image segmentation algorithms. To perform an image segmentation task, several techniques have been developed. One of simple and flexible technique is discussed in this book from basics. This technique is known as variational modeling for image segmentation. This technique can help readers to work in other image processing tasks as well, such as image denoising, image inpainting, image debluring, image recognition, image registration.
Subramaniam Ganesan Model based design of Adaptive Noise Cancellation Subramaniam Ganesan Model based design of Adaptive Noise Cancellation Новинка

Subramaniam Ganesan Model based design of Adaptive Noise Cancellation

9739 руб.
This book demonstrates the implementation of an improved adaptive Wiener filter on Texas Instruments TMS 320C6713 DSK board. A performance comparison of an improved adaptive Wiener filter with Lee's adaptive Wiener filter is illustrated. the profile parameters of the auto-code generated by the Real Time workshop for the Simulink model of LMS filter on TI C6713 DSK is compared with the C implementation of LMS filter on C6713. A LabVIEW model of adaptive noise cancellation based on an improved adaptive Wiener filter is implemented on C6713 using TIDSP Test Integration Tool kit.
Ashish Tewari Adaptive Aeroservoelastic Control Ashish Tewari Adaptive Aeroservoelastic Control Новинка

Ashish Tewari Adaptive Aeroservoelastic Control

10845.5 руб.
This is the first book on adaptive aeroservoelasticity and it presents the nonlinear and recursive techniques for adaptively controlling the uncertain aeroelastic dynamics Covers both linear and nonlinear control methods in a comprehensive manner Mathematical presentation of adaptive control concepts is rigorous Several novel applications of adaptive control presented here are not to be found in other literature on the topic Many realistic design examples are covered, ranging from adaptive flutter suppression of wings to the adaptive control of transonic limit-cycle oscillations
Abdeljalil Gattal Segmentation-Verification for Handwritten Digit Recognition Abdeljalil Gattal Segmentation-Verification for Handwritten Digit Recognition Новинка

Abdeljalil Gattal Segmentation-Verification for Handwritten Digit Recognition

6252 руб.
Doctoral Thesis / Dissertation from the year 2016 in the subject Computer Science - Applied, National Higher School Of Computer Engineering, language: English, abstract: Automatic reading of digit fields from an image document has been proposed in several applications such as bank checks, postal code and forms. In this context, two main problems occur when attempting to design a handwritten digit string recognition system. The first problem is the link between adjacent digits, which can be naturally spaced, overlapped or/and connected. The second problem is the unknown length of the digit string, which is not carefully written by people in real-life situations.In this thesis, SVM-based segmentation-verification system for segmenting two connected handwritten digits using the oriented sliding window is proposed. It employs a segmentation-verification system using conjointly the oriented sliding window and Support Vector Machine (SVM) classifiers. Experimental results showed that the proposed system is more appropriate for segmenting simple and multiple connections. Its main advantage lays in the use few rules for finding the optimal segmentation path. Hence, the proposed approach constitutes a tradeoff between the correct segmentation and the number of the segmentation cuts. Thereafter, we propose a new design of a handwritten digit string recognition system based on the explicit approach for the unknown-length digit strings. Three methods are combined according the link of ad...
Ekins Sean The Agile Approach to Adaptive Research. Optimizing Efficiency in Clinical Development Ekins Sean The Agile Approach to Adaptive Research. Optimizing Efficiency in Clinical Development Новинка

Ekins Sean The Agile Approach to Adaptive Research. Optimizing Efficiency in Clinical Development

7709.04 руб.
Apply adaptive research to improve results in drug development The pharmaceutical industry today faces a deepening crisis: inefficiency in its core business, the development of new drugs. The Agile Approach to Adaptive Research offers a solution. It outlines how adaptive research, using already-available tools and techniques, can enable the industry to streamline clinical trials and reach decision points faster and more efficiently. With a wealth of real-world cases and examples, author Michael Rosenberg gives readers a practical overview of drug development, the problems inherent in current practices, and the advantages of adaptive research technology and methods. He explains the concepts, principles, and specific techniques of adaptive research, and demonstrates why it is an essential evolutionary step toward improving drug research and development. Chapters explore such subjects as: The adaptive concept Design and operational adaptations Sample-size reestimation Agile clinical development Safety and dose finding Statistics in adaptive research, including frequentist and Bayesian approaches Data management technologies The future of clinical development By combining centuries-old intellectual foundations, recent technological advances, and modern management techniques, adaptive research preserves the integrity and validity of clinical research but dramatically improves efficiency.
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840 руб.
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979 руб.
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840 руб.
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840 руб.
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840 руб.
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979 руб.
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840 руб.
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Simon Moore Digital Wealth. An Automatic Way to Invest Successfully Simon Moore Digital Wealth. An Automatic Way to Invest Successfully Новинка

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Leverage algorithms to take your investment approach to the next level Digital Wealth: An Automatic Way to Invest Successfully reveals core investment strategies that you can leverage to build long-term wealth. More than a simple review of traditional investment strategies, this innovative text proffers digital investment techniques that are driven not by people but by algorithms. Supported by asset allocation research, the secrets shared in this forward-thinking book have underpinned cutting-edge investment firms as they integrate algorithm-based strategies. In addition to presenting key concepts, this groundbreaking resource explains how these concepts can give you an edge over the professionals on Wall Street through details regarding achieving financial security and meeting financial goals rooted in a firm foundation in behavioral finance, portfolio tilts, and modern portfolio theory. Investment strategies have evolved from one generation to the next, and the ability to leverage new digital tools calls for another overhaul of traditional investment concepts. Investment techniques implemented by algorithm rather than by human monitoring can, in some cases, prove more successful. The key to a balanced portfolio is understanding what these algorithm-based strategies are, and how to best use them. Explore insights from multiple Nobel Prize winning academics that can give your investment strategy an edge Consider how technology can open up powerful techniques to mainstream investors, including tax-loss harvesting and automated rebalancing Discuss how cost minimization and a strategic tax approach can boost your portfolio's compound growth Identify strategies that support the long-term growth of your wealth Digital Wealth: An Automatic Way to Invest Successfully is an essential text for sophisticated individual investors and investment consultants alike who want to explore how digital tools can bolster financial success.
David Mödinger Decoding Gabidulin Codes Using Module Minimization David Mödinger Decoding Gabidulin Codes Using Module Minimization Новинка

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6052 руб.
Master's Thesis from the year 2015 in the subject Computer Science - General, grade: 1,0, University of Ulm (Institut für Nachrichtentechnik), language: English, abstract: The thesis provides an introduction to Reed-Solomon and Gabidulin Codes as well as the decoding technique known as module minimization. Within the thesis the algorithm of Alekhnovich, known for fast decoding of Reed-Solomon codes, is extended and proven for general Ore Extensions. The runtime of the algorithm is further analysed within the constraints of module minimization.
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Leverage algorithms to take your investment approach to the next level Digital Wealth: An Automatic Way to Invest Successfully reveals core investment strategies that you can leverage to build long-term wealth. More than a simple review of traditional investment strategies, this innovative text proffers digital investment techniques that are driven not by people but by algorithms. Supported by asset allocation research, the secrets shared in this forward-thinking book have underpinned cutting-edge investment firms as they integrate algorithm-based strategies. In addition to presenting key concepts, this groundbreaking resource explains how these concepts can give you an edge over the professionals on Wall Street through details regarding achieving financial security and meeting financial goals rooted in a firm foundation in behavioral finance, portfolio tilts, and modern portfolio theory. Investment strategies have evolved from one generation to the next, and the ability to leverage new digital tools calls for another overhaul of traditional investment concepts. Investment techniques implemented by algorithm rather than by human monitoring can, in some cases, prove more successful. The key to a balanced portfolio is understanding what these algorithm-based strategies are, and how to best use them. Explore insights from multiple Nobel Prize winning academics that can give your investment strategy an edge Consider how technology can open up powerful techniques to mainstream investors, including tax-loss harvesting and automated rebalancing Discuss how cost minimization and a strategic tax approach can boost your portfolio's compound growth Identify strategies that support the long-term growth of your wealth Digital Wealth: An Automatic Way to Invest Successfully is an essential text for sophisticated individual investors and investment consultants alike who want to explore how digital tools can bolster financial success.
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