moratorium 发表于 2025-3-28 17:26:29

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Pathogen 发表于 2025-3-28 19:33:09

A Low-Power Neuromorphic System for Real-Time Visual Activity Recognition platforms that can detect even small objects and activities with high-accuracy. Our system modifies and integrates multiple independent algorithms into an end-to-end system consisting of five primary modules: object detection, object tracking, convolutional neural network image feature extractor, r

使坚硬 发表于 2025-3-29 00:08:33

Video-Based Human Action Recognition Using Kernel Relevance Analysisline employed in action recognition, with a two-fold post-processing stage: (i) A descriptor relevance ranking based on the centered kernel alignment (CKA) algorithm to match trajectory-aligned descriptors with the output labels (action categories), and (ii) a feature embedding based on the same alg

incision 发表于 2025-3-29 05:06:28

Robust Incremental Hidden Conditional Random Fields for Human Action Recognitionhuman action. However, finding the optimal number of hidden states remains a severe limitation for this model. This paper addresses this limitation by proposing a new model, called robust incremental hidden conditional random field (RI-HCRF). A hidden Markov model (HMM) is created for each observati

极力证明 发表于 2025-3-29 07:54:19

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Somber 发表于 2025-3-29 15:27:33

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惰性女人 发表于 2025-3-29 18:18:56

Gender Classification Based on Facial Shape and Texture Features Local Binary Pattern (LBP) and Local Directional Pattern (LDP). A gender classification model based on the fusion of appearance and shape features is proposed. The experimental results show that the fusion of the LBP and LDP with the Active Shape Model improved the gender classification accuracy ra

legislate 发表于 2025-3-29 23:26:21

Advances in Visual Computing978-3-030-03801-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

FADE 发表于 2025-3-30 00:02:08

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贞洁 发表于 2025-3-30 06:32:24

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查看完整版本: Titlebook: Advances in Visual Computing; 13th International S George Bebis,Richard Boyle,Jonathan Ventura Conference proceedings 2018 Springer Nature