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This book covers aspects of human re-identification problems related to computer vision and machine learning. Working from a practical perspective, it introduces novel algorithms and designs for human re-identification that bridge the gap between research and reality. The primary focus is on building a robust, reliable, distributed and scalable smart surveillance system that can be deployed in real-world scenarios. This book also includes detailed discussions on pedestrian candidates detection, discriminative feature extraction and selection, dimension reduction, distance/metric learning, and decision/ranking enhancement. This book is intended for professionals and researchers working in computer vision and machine learning. Advanced-level students of computer science will also find the content valuable.

Computer science. --- Computer communication systems. --- Multimedia information systems. --- Artificial intelligence. --- Image processing. --- Computer Science. --- Image Processing and Computer Vision. --- Artificial Intelligence (incl. Robotics). --- Multimedia Information Systems. --- Computer Communication Networks. --- Computer vision. --- Pattern recognition systems. --- Electronic surveillance. --- Machine vision --- Vision, Computer --- Electronics in surveillance --- SIGINT (Electronic surveillance) --- Signals intelligence --- Surveillance, Electronic --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Remote sensing --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Multimedia systems. --- Artificial Intelligence. --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Optical data processing. --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Distributed processing --- Optical equipment

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This book is a collection of the accepted papers presented at the Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) in conjunction with the 36th AAAI Conference on Artificial Intelligence 2022. During AIBSD 2022, the attendees addressed the existing issues of data bias and scarcity in Artificial Intelligence and discussed potential solutions in real-world scenarios. A set of papers presented at AIBSD 2022 is selected for further publication and included in this book.

Technology: general issues. --- Artificial intelligence --- History of engineering & technology. --- permutation equivariance --- optimization --- gender bias --- fairness --- face-recognition models --- facial attributes --- social bias --- bias detection --- natural language processing --- temporal bias --- forecasting --- contrastive learning --- supervised contrastive learning --- transfer learning --- robustness --- noisy labels --- coresets --- deep learning --- contextualized embeddings --- out-of-distribution generalization

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• Reference Manager
• EndNote
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This book is a collection of the accepted papers presented at the Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) in conjunction with the 36th AAAI Conference on Artificial Intelligence 2022. During AIBSD 2022, the attendees addressed the existing issues of data bias and scarcity in Artificial Intelligence and discussed potential solutions in real-world scenarios. A set of papers presented at AIBSD 2022 is selected for further publication and included in this book.

Artificial intelligence --- permutation equivariance --- optimization --- gender bias --- fairness --- face-recognition models --- facial attributes --- social bias --- bias detection --- natural language processing --- temporal bias --- forecasting --- contrastive learning --- supervised contrastive learning --- transfer learning --- robustness --- noisy labels --- coresets --- deep learning --- contextualized embeddings --- out-of-distribution generalization