This paper proposes a new model, kernelized dual regression (KDR), based on DLRC and the kernel trick which is a useful technique in image classification.
To address this problem, Gao et al. [13] propose kernel dual linear regression model to improve the classification performance and overcome the limitation that�...
KDLRC is a nonlinear version of DLRC and can overcome the drawback ofDLRC, which first embeds the input data into a high-dimensional Hilbert space,�...
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In this paper, based on the concept of dual linear regression classification method for image set classification, we propose a novel discriminative framework.
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... classification, object categorization, and palmprint ... Kernelized dual regression incorporating local information for image set classification.
Abstract. With significant advances in imaging technology, multiple images of a person or an object are becoming readily available.
Wang, Kernelized dual regression incorporating local information for image set classification, Pattern Recognition Letters, № 140, с. 274 https://doi.org�...
We demonstrate our algorithm on both classification and regression tasks, including object recognition, 3-D human pose inference, and time of publication�...
Sep 17, 2020 � In this paper, we present a group-based local adaptive deep multiple kernel learning (GLDMKL) method with lp norm.