Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics / / edited by Jianping Gou [and three others].

• TeilnehmendeR: Gou, Jianping,
• Place / Publishing House: Basel, Switzerland : : MDPI - Multidisciplinary Digital Publishing Institute,, [2023]; ©2023
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (556 pages)
• Hierarchical level: Monograph
• Statement of Responsibility: edited by Jianping Gou [and three others].

The present reprint contains 33 articles accepted and published in the Special Issue entitled "Advancement of Mathematical Methods in Feature Representation Learning for Artificial Intelligence, Data Mining and Robotics, 2022" in the MDPI journal, Mathematics, which covers a wide range of topics connected to the theory and applications of feature representation learning for image processing, artificial intelligence, data mining and robotics. These topics include, among others, elements from image blurring, image aesthetic quality assessment, pedestrian detection, visual tracking, vehicle re-identification, face recognition, 3D reconstruction, the stability of switched systems, domain adaption, deep reinforcement, sentiment analysis, graph convolutional networks, knowledge graphs, geometric metric learning, etc. It is hoped that this reprint will be interesting and useful for those working in the area of image processing, computer vision, machine learning, natural language processing and robotics, as well as for those with backgrounds in machine learning who are willing to become familiar with recent advancements in artificial intelligence, which, today, is present in almost all aspects of human life and activities.