Cited By
View all- Qian YZhang ZZhao PZhou Z(2024)Learning with Asynchronous LabelsACM Transactions on Knowledge Discovery from Data10.1145/366218618:8(1-27)Online publication date: 31-Jul-2024
While recent techniques for discriminative dictionary learning have demonstrated tremendous success in image analysis applications, their performance is often limited by the amount of labeled data available for training. Even though labeling images is ...
In this paper we study multi-label learning with weakly labeled data, i.e., labels of training examples are incomplete, which commonly occurs in real applications, e.g., image classification, document categorization. This setting includes, e.g., (i) ...
Deep convolutional neural networks have been highly effective in segmentation tasks. However, high performance often requires large datasets with high-quality annotations, especially for segmentation, which requires precise pixel-wise labelling. ...
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