The virtual-to-real paradigm, ie, training models on virtual data and then applying them to
solve real-world problems, has attracted more and more attention from various domains by …

Deep learning algorithms have exhibited impressive performance across various computer
vision tasks; however, the challenge of overfitting persists, especially when dealing with …

In semi-supervised learning, unlabeled samples can be utilized through augmentation and
consistency regularization. However, we observed certain samples, even undergoing strong …

Recently a number of image-mixing-based augmentation techniques have been introduced
to improve the generalization of deep neural networks. In these techniques two or more …

Person re-identification (Re-ID) subject to loss of detailed information (sacrificing certain
intricate body details) in samples caused by conventional regularization algorithms and …

Class-incremental learning (CIL) has emerged as a means to learn new classes
incrementally without catastrophic forgetting of previous classes. Recently, CIL has …

Bovine respiratory disease (BRD) is the leading cause of death in calves. Abnormal
respiratory behavior (ARB) is one of the prevalent clinical signs of BRD in calves …

Remote sensing (RS) change detection (CD) for open-pit mines plays a critical role in both
mineral development and environmental conservation. The performance of supervised deep …

In communication between humans, gestures are often preferred or complementary to
verbal expression since the former offers better spatial referral. Finger pointing gesture …

Low-level vision plays a crucial role in a wide range of imaging quality and image
recognition applications. However, the limited size, quality, and diversity of datasets often …