標題: Titlebook: Machine-based Intelligent Face Recognition; Dengpan Mou Book 2010Latest edition Springer-Verlag Berlin Heidelberg 2010 Face Recognition.HE [打印本頁] 作者: 突然 時間: 2025-3-21 18:39
書目名稱Machine-based Intelligent Face Recognition影響因子(影響力)
書目名稱Machine-based Intelligent Face Recognition影響因子(影響力)學(xué)科排名
書目名稱Machine-based Intelligent Face Recognition網(wǎng)絡(luò)公開度
書目名稱Machine-based Intelligent Face Recognition網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Machine-based Intelligent Face Recognition被引頻次
書目名稱Machine-based Intelligent Face Recognition被引頻次學(xué)科排名
書目名稱Machine-based Intelligent Face Recognition年度引用
書目名稱Machine-based Intelligent Face Recognition年度引用學(xué)科排名
書目名稱Machine-based Intelligent Face Recognition讀者反饋
書目名稱Machine-based Intelligent Face Recognition讀者反饋學(xué)科排名
作者: adequate-intake 時間: 2025-3-21 20:41
Springer-Verlag Berlin Heidelberg 2010作者: 過分 時間: 2025-3-22 01:55
Dengpan MouDiscusses the general engineering methods for imitating intelligent human brains for video-based face recognition that is completely unsupervised, self-adaptive and robust.All cues are combined togeth作者: 紀念 時間: 2025-3-22 08:21 作者: anaerobic 時間: 2025-3-22 10:26
https://doi.org/10.1007/978-3-642-00751-4Face Recognition; HEP; Intelligent Face Recognition; Self-adaptive; Self-learning作者: FIS 時間: 2025-3-22 16:02
Introduction,ing point of this book, we are discussing the fundamental pros and cons of state-of-the-art machine vision system versus its human being counterpart. Inspired from the comparison, in the second part of this chapter, a machine-based intelligent face recognition system is briefly introduced. With the 作者: palette 時間: 2025-3-22 17:25
Fundamentals and Advances in Biometrics and Face Recognition,ures and categories are defined and overviewed. This is followed in section 2 by the brief introduction and surveys on current cognitive science research. The essential point here is the fundamental intelligence of human brains. In section 3, machine-based biometric recognition tasks and methods are作者: 支柱 時間: 2025-3-23 00:41
Combined Face Detection and Tracking Methods,ep for an intelligent, automatic and unsupervised face recognition system. In section 1, the proposals of face detection are briefly overviewed. Imagedbased face detection issues are discussed in section 2, including the choice of detection algorithms, the definition of face region based on the eye 作者: 火光在搖曳 時間: 2025-3-23 02:15
Automatic Face Recognition,n-related sub-steps of the enrollment procedure, including same face decision, feature extraction and encoding. If each single step is running passively, the autonomous procedure of recognition is guaranteed. After the introduction section, feature extraction and encoding methods are briefly covered作者: 歡騰 時間: 2025-3-23 06:46
Unsupervised Face Database Construction,arning background is introduced in section 2, including supervised as well as unsupervised learning methods, and the analysis of typical clustering structures. In section 3, a proposed data structure is described, where the fused clustering structure and its related parameters for building the face 作者: HALO 時間: 2025-3-23 12:32
State Machine Based Automatic Procedure,whole automatic and self-learning system. The major points are how to define different states and how to define their corresponding transitions. By utilizing the combined information such as video context, temporal information, and logic analysis, an efficient and stable state machine structure is p作者: Extemporize 時間: 2025-3-23 17:56
System Implementation,troduction section, in section 2, the typical required hardware configuration is presented. Section 3 is regarding the software implementation, where two versions are designed for different demonstration purposes: online and offline versions. Technology dependent parameters which have to be consider作者: Feckless 時間: 2025-3-23 18:37 作者: 閃光你我 時間: 2025-3-23 22:18 作者: 效果 時間: 2025-3-24 04:41 作者: 小口啜飲 時間: 2025-3-24 06:46 作者: etidronate 時間: 2025-3-24 14:31 作者: 通便 時間: 2025-3-24 15:03
Combined Face Detection and Tracking Methods, definition of “search region” and the analysis of temporal change, the motion-based face detector can significantly benefit from the temporal context from video sequences. Summary and future research directions are the final parts of this chapter.作者: 有害處 時間: 2025-3-24 21:56 作者: GROG 時間: 2025-3-24 23:13
Conclusions and Future Directions, the system can deal with major challenging limitations in the state-of-the-art face recognition research: the aging problem, the difficulty of no better recognition quality in videos than in images, and the weakness of dealing with head pose variations.作者: 慷慨不好 時間: 2025-3-25 04:43
Book 2010Latest editionition in a fundamental way, which is completely unsupervised, automatic, self-learning, self-updated and robust. It also overviews state-of-the-art research on cognitive-based biometrics and machine-based biometrics, and especially the advances in face recognition...This book is intended for scienti作者: 精美食品 時間: 2025-3-25 11:02 作者: 英寸 時間: 2025-3-25 13:09 作者: 血友病 時間: 2025-3-25 17:20 作者: hangdog 時間: 2025-3-25 23:42 作者: seduce 時間: 2025-3-26 02:01
gence, and particularly of face recognition...Dr. Dengpan Mou, Dr.-Ing. and MSc from University of Ulm, Germany, is with Harman/Becker Automotive Systems GmbH, working on video processing, computer vision and machine learning research and development topics..作者: muffler 時間: 2025-3-26 05:31
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