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Computer Vision: A Reference Guide, Second Edition

Posted By: AvaxGenius
Date: 13 Oct 2021 03:28:03
Computer Vision: A Reference Guide, Second Edition

Computer Vision: A Reference Guide, Second Edition by Katsushi Ikeuchi
English | PDF,EPUB | 2021 | 1436 Pages | ISBN : 3030634159 | 278 MB

This comprehensive reference provides easy access to relevant information on all aspects of Computer Vision. An A-Z format of over 240 entries offers a diverse range of topics for those seeking entry into any aspect within the broad field of Computer Vision. Over 200 Authors from both industry and academia contributed to this volume.
3D Feature Action Recognition Active Camera Calibration Active Computer Vision Active Contours Active Object Recognition Active Perception Active Sensor Active Stereo Vision Active Vision Activity Analysis Activity Recognition AdaBoost Adaptive Gains Adversarial Networks Affine Camera Algebraic Curve Algebraic Surface Algorithm algorithms Algorithms Analytic Reflectance Functions Animat Vision Appearance Scanning Appearance-Based Human Tracking Automatic Gait Recognition Boosting Algorithm C Calculus Calculus of Variations Calibration Camera Calibration Camera Pose Chemical Imaging Clifford Algebra Cluster Sampling Cognitive Vision Color Adaptation Computer Science Computer Vision Curves Data Augmentation Data Fusion Deep Image Stylization Multi-camera Human Action Recognition Object Recognition Optic Flow Science Swendsen-Wang Algorithm Variational Analysis
Details

Decision Trees, Random Forests, AdaBoost & XGBoost in Python

Posted By: Sigha
Date: 14 Dec 2019 11:06:24
Decision Trees, Random Forests, AdaBoost & XGBoost in Python

Decision Trees, Random Forests, AdaBoost & XGBoost in Python
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 2.25 GB
Genre: eLearning Video | Duration: 7 hours | Language: English

Decision Trees and Ensembling techniques in Python. How to run Bagging, Random Forest, GBM, AdaBoost & XGBoost in Python
Details
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