Constituent
发表于 2025-3-26 23:30:19
Consensus for Decomposable Measuresfall detection benchmark dataset containing 60 occluded falls for which the end of the fall is completely occluded. We also evaluate four existing fall detection methods using a single depth camera on this benchmark dataset.
ONYM
发表于 2025-3-27 01:34:24
Conference proceedings 2014s systems, medical imaging, tracking for human activity monitoring, intelligent transportation systems, visual perception and robotic systems. Part II (LNCS 8888) comprises topics such as computational bioimaging , recognition, computer vision, applications, face processing and recognition, virtual reality, and the poster sessions.
公式
发表于 2025-3-27 07:45:53
Vikram Gulati,Anil K. Maheshwarih based technique, higher speed was achieved compared to pixel-based curvature registration technique with fast DCT solver. The implementation was done in MATLAB without any specific optimization. Higher speeds can be achieved using C/C++ implementations.
habile
发表于 2025-3-27 12:51:00
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枕垫
发表于 2025-3-27 14:02:31
Consensus versus Dichotomous Votingerimental validation on synthetic and real-world imagery datasets and demonstrated better performance of the cascade tree-based model over the original grid-structured CRF model with loopy belief propagation inference.
Blemish
发表于 2025-3-27 20:41:26
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Presbycusis
发表于 2025-3-27 22:06:20
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fatty-acids
发表于 2025-3-28 02:05:58
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脆弱么
发表于 2025-3-28 08:40:53
Fast Mesh-Based Medical Image Registrationh based technique, higher speed was achieved compared to pixel-based curvature registration technique with fast DCT solver. The implementation was done in MATLAB without any specific optimization. Higher speeds can be achieved using C/C++ implementations.
Carbon-Monoxide
发表于 2025-3-28 14:29:33
One-Shot Learning of Sketch Categories with Co-regularized Sparse Codinggories and transfer them to unseen categories. We contribute a new dataset consisting of 7,760 human segmented sketches from 97 object categories. Extensive experiments reveal that the proposed method can classify unseen sketch categories given just one training sample with a 33.04% accuracy, offering a two-fold improvement over baselines.