Xiaoyu Liu, Yong Hu*
CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4413-4432, 2024, DOI:10.32604/cmc.2024.053938
Abstract Multi-label image classification is recognized as an important task within the field of computer vision, a discipline that has experienced a significant escalation in research endeavors in recent years. The widespread adoption of convolutional neural networks (CNNs) has catalyzed the remarkable success of architectures such as ResNet-101 within the domain of image classification. However, in multi-label image classification tasks, it is crucial to consider the correlation between labels. In order to improve the accuracy and performance of multi-label classification and fully combine visual and semantic features, many existing studies use graph convolutional networks (GCN) for… More >
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