Jan 30, 2024 · The experimental results show that this method effectively improves the classification accuracy for video semantic analysis and shorten the time ...
A video semantic concept classification approach based on sparse coefficient vector (SCV) and a kernel-based weighted KNN (KWKNN) is proposed in this paper.
The experimental results show that this method effectively improves the classification accuracy for video semantic analysis and shorten the time used in the ...
The experimental results show that this method effectively improves the classification accuracy for video semantic analysis and shorten the time used in the ...
ABSTRACT. Video semantic concept analysis has received a lot of research attention in the area of human computer interactions in recent times.
A Discriminative Locality-Sensitive Dictionary Learning With Kernel ...
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Finally, this paper modifies the vote results combined with the kernel weight coefficient of each class and determine the video semantic concept. The ...
A Discriminative LocalitySensitive Dictionary Learning With Kernel Weighted KNN Classification for Video Semantic Concepts Analysis. ; Authors. Ghansah, B., ...
To further improve the accuracy of video semantic classification, a VSC classification approach based on Sparse Coefficient Vector and a Virtual Kernel-based ...
A locality-sensitive discriminative dictionary learning and SR based on kernel sparsity is mainly made for face recognition that embeds image features ...
Apr 1, 2019 · In this paper, a new kernel based approach; named Video Semantic Analysis based Kernel Locality-Sensitive Discriminative Sparse Representation (KLSDSR) is ...