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Machine Learning for Vision-Based Motion Analysis: Theory and Techniques

to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights;

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Intelligent Information and Database Systems

Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics;

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Intelligent Information and Database Systems

; Decision Support and Control Systems; Machine Learning and Data Mining; Computer Vision Techniques; Advanced Data Mining Techniques and;

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine;

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Computer Analysis of Images and Patterns

and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Computer Vision for UAV, DL-UAV 2019;

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Image Analysis and Recognition

computing; image enhancement and reconstruction; image segmentation; motion and tracking; 3D computer vision; feature extraction; detection and;

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Learn Computer Vision Using Opencv: With Deep Learning Cnns and Rnns

vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an;

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Intelligent Information and Database Systems

; Decision Support and Control Systems; Machine Learning and Data Mining; Computer Vision Techniques; Advanced Data Mining Techniques and;

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Intelligent Information and Database Systems

, technology opportunity, e-learning, and fuzzy intelligent systems; analysis for image, video and motion data in life sciences; real world;

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Intelligent Information and Database Systems

, technology opportunity, e-learning, and fuzzy intelligent systems; analysis for image, video and motion data in life sciences; real world;

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Statistical and Machine Learning Approaches for Network Analysis

weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross;

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Handbook of Image Processing and Computer Vision

comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The;

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining;

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Mastering OpenCV 4 with Python

Create computer vision and deep learning web applications Who this book is forThis book is designed for computer vision developers, engineers;

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Advanced Image and Video Processing Using MATLAB

topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image;

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Rank-Based Methods for Shrinkage and Selection

Rank-Based Methods for Shrinkage and Selection A practical and hands-on guide to the theory and methodology of statistical estimation based;

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Advanced Machine Vision Paradigms for Medical Image Analysis

of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision;

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Machine Vision Inspection Systems

, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry;

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Proceedings of 2nd International Conference on Computer Vision Image Processin

models for image/video processing; machine learning in image/video analysis; probability and uncertainty handling for image/video processing;

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Python Machine Learning

Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning;

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TensorFlow Machine Learning Cookbook

learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading;

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Classification, Parameter Estimation and State Estimation

techniques and technologies for machine learning in computer vision systems, including: * PRTools5 software for MATLAB especially the latest;

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Image Correlation for Shape Motion and Deformation Measurements

new methods for quantitative error estimates in correlation-based motion measurements, and the effect of out-of-plane motion on 2D;

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Image Correlation for Shape, Motion and Deformation Measurements

new methods for quantitative error estimates in correlation-based motion measurements, and the effect of out-of-plane motion on 2D;

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Challenges and Applications for Implementing Machine Learning in Computer Vision

efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a;

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Challenges and Applications for Implementing Machine Learning in Computer Vision

efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a;

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Dynamic Vision for Perception and Control of Motion

representations of motion for hypothesized objects whose parameters are adjusted by well-known prediction error feedback and recursive estimation;

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