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3D Shape Analysis - Fundamentals, Theory, and Applications

feature descriptors, and algorithms) that are commonly used for the detection, registration, recognition, classification, and retrieval of 3D;

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A Theory of Shape Identification

image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability;

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Geometric Constraints for Object Detection and Delineation

on object shape or scene content, presenting serious obstacles for the development of robust object detection and delineation techniques;

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Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS

of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected;

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Data Mining from Multimedia and Human Behavioral Data

Object recognitiondetection has always been a challenging topic for both computer scientists and psychologists. We study the categorical;

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Hierarchical Micro/Nanostructured Materials

/nanostructured materials, the first section begins with a detailed discussion of the methods of mass production for hierarchical micro/nanostructured;

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Hierarchical Micro/Nanostructured Materials

/nanostructured materials, the first section begins with a detailed discussion of the methods of mass production for hierarchical micro/nanostructured;

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OpenCV Android Programming By Example

vision-aware applications using OpenCV, then this book is definitely for you. It would be very helpful if you understand the basics of image;

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Probabilistic and Biologically Inspired Feature Representations

combination of properties, channel representations become a visual Swiss army knife-they can be used for image enhancement, visual object tracking, as;

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Probabilistic and Biologically Inspired Feature Representations

combination of properties, channel representations become a visual Swiss army knife-they can be used for image enhancement, visual object tracking, as;

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Hands-On Image Processing with Python

enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn;

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Fuzzy Approach to Hierarchical Clustering

for cluster analysis, to extend the definition of object dissimilarity for the case of fuzzy objects; to realize clustering of fuzzy data, to;

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Object Tracking in Distributed Video Networks

efficiently due to inherent assumptions of constancy of attributes. Our approach assumes an environment where the object attributes may vary. The;

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Deep Learning and Convolutional Neural Networks for Medical Image Computing

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation;

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Fourier Descriptors and their Applications in Biology

The purpose of this book is to introduce Fourier descriptors as a method for measuring the shape of whole or parts of organisms. Fourier;

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Fourier Descriptors and their Applications in Biology

The purpose of this book is to introduce Fourier descriptors as a method for measuring the shape of whole or parts of organisms. Fourier;

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Computer Vision

The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object;

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Computer Vision

The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object;

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A Pyramid Framework for Early Vision

, approach to vision, including its theoretical foundations, a set of pyramid-based modules for image processing, object detection, texture;

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Moving Object Detection Using Background Subtraction

well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and;

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Python Descriptors

descriptor protocol, the author delves into using and creating descriptors in practice, with plenty of tips, patterns, and real-world guidance;

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Video object Tracking

, and camera motion.The work carried out implements object tracking using mean shift based algorithm and feature based algorithm for an;

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

, you'll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed;

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