3 accepted papers
Unsupervised domain adaptive object detection (DAOD) aims to adapt detectors from a labeled source domain to an unlabelled target domain. Existing DAOD works learn feature representations with both class discriminative and domain invariant by jointly minimizing the loss across domain alignment and…
Understanding and analyzing animal behavior is increasingly essential to protect endangered animal species. However, the application of advanced computer vision techniques in this regard is minimal, which boils down to lacking large and diverse datasets for training deep models. To break the deadloc…
Deep learning algorithms are recognized as the most effective method for rectal tumor segmentation. However, since the multi-scale detailed feature information of rectal tumor cannot be fully extracted and applied, the segmentation and identification results of most algorithms are not always perfect…