3 accepted papers
Robots are increasingly envisioned as human companions, assisting with everyday tasks that often involve manipulating deformable objects. Recent advancements in robotic hardware and embodied AI algorithms have expanded the range of tasks robots can perform. However, current systems still struggle wi…
Domain adaptation aims to build up an adaptive model for the learning tasks on target domain by using the data from source domain. Existing domain adaptation methods focused on reducing the gap between the data distributions of source domain and target domain but neglected the uncertainty of source…
Histopathology image analysis plays a critical role in cancer diagnosis and treatment. To automatically segment the cancerous regions, fully supervised segmentation algorithms require labor-intensive and time-consuming labeling at the pixel level. In this research, we propose CAMEL, a weakly supervi…