Aug 22, 2014 · We investigate an image classification task where training images come along with tags, but only a subset being labeled, and the goal is to ...
We investigate an image classification task where training images come along with tags, but only a subset being labeled, and the goal is to predict the ...
We investigate an image classification task where training images come along with tags, but only a subset being labeled, and the goal is to predict the ...
To handle the task more effectively, we propose to combine tag refinement, graph-based learning and support vector regression together. Experimental results on ...
Aug 22, 2014 · We investigate an image classification task where training images come along with tags, but only a subset being labeled, and the goal is to ...
[PDF] Graph-based multimodal semi-supervised image classification ...
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An adaptive multimodal hypergraph learning method (AMH) is proposed that uses multiple neighborhoods method to avoid generating a k-uniform hyperedge, ...
To handle the task more effectively, we propose to combine tag refinement, graph- based learning and support vector regression together. Experimental results on ...
Feb 26, 2021 · Abstract—Semi-supervised learning (SSL) has tremendous value in practice due to its ability to utilize both labeled data.
Multimodal semi-supervised image classification by combining tag refinement, graph-based learning and support vector regression ; MULTIMODAL SEMI-SUPERVISED ...
Wenxuan Xie, Zhiwu Lu , Yuxin Peng, Jianguo Xiao: Graph-based multimodal semi-supervised image classification. Neurocomputing 138: 167-179 (2014).