Food is essential for human life and it is fundamental to the human experience. Food-related
study may support multifarious applications and services, such as guiding human behavior …

Over the past decades, medical image analytics was greatly facilitated by the explosion of
digital imaging techniques, where huge amounts of medical images were produced with …

Delicate feature representation about object parts plays a critical role in fine-grained
recognition. For example, experts can even distinguish fine-grained objects relying only on …

Fine-grained classification is a challenging problem, due to subtle differences among highly-
confused categories. Most approaches address this difficulty by learning discriminative …

Deep metric learning has gained much popularity in recent years, following the success of
deep learning. However, existing frameworks of deep metric learning based on contrastive …

Automated breast cancer multi-classification from histopathological images plays a key role
in computer-aided breast cancer diagnosis or prognosis. Breast cancer multi-classification is …

The modern image search system requires semantic understanding of image, and a key yet
under-addressed problem is to learn a good metric for measuring the similarity between …

Attention-based learning for fine-grained image recognition remains a challenging task,
where most of the existing methods treat each object part in isolation, while neglecting the …

Abstract Vehicle Re-identification (ReID) is of great significance to the intelligent
transportation and public security. However, many challenging issues of Vehicle ReID in …

Recognizing objects from subcategories with very subtle differences remains a challenging
task due to the large intra-class and small inter-class variation. Recent work tackles this …