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978-1-4471-7119-5Springer-Verlag London Limited 2011商品 发表于 2025-3-23 22:20:09
Zerebrale Aneurysmen und GefäßmalformationenThis chapter provides an introduction to face recognition research. Main steps of face recognition processing are described. Face detection and recognition problems are explained from a face subspace viewpoint. Technology challenges are identified after that. Typical strategies for solving the problems are suggested.Interim 发表于 2025-3-24 05:25:31
Introduction,This chapter provides an introduction to face recognition research. Main steps of face recognition processing are described. Face detection and recognition problems are explained from a face subspace viewpoint. Technology challenges are identified after that. Typical strategies for solving the problems are suggested.NATAL 发表于 2025-3-24 06:49:33
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Face Subspace Learningral mean criteria and the max-min distance analysis (MMDA) algorithm; manifold learning algorithms, including the discriminative locality alignment (DLA) and manifold elastic net (MEN); and the transfer subspace learning framework. Experiments on face recognition are also provided.indubitable 发表于 2025-3-24 18:40:53
Local Representation of Facial Featureses to describe faces for recognition, verification, localization, or detection, is a fundamental problem in face biometrics. In this chapter, we review the most popular and successful features for face biometrics. In general, one should include complete algorithms when comparing the features, but ce违法事实 发表于 2025-3-24 20:23:45
Zerebrale Gefäßkrankheiten im Alterer vision research in general, has witnessed a growing interest in techniques that capitalize on this observation and apply algebraic and statistical tools for extraction and analysis of the underlying manifold. In this chapter, we describe in roughly chronologic order techniques that identify, para伟大 发表于 2025-3-25 02:05:16
https://doi.org/10.1007/978-3-662-10993-9ral mean criteria and the max-min distance analysis (MMDA) algorithm; manifold learning algorithms, including the discriminative locality alignment (DLA) and manifold elastic net (MEN); and the transfer subspace learning framework. Experiments on face recognition are also provided.