Classical multiple instance learning (MIL) methods are often based on the identical and independent distributed assumption between instances, hence neglecting potentially rich contextual information beyond individual entities. On other hand, Transformers with global self-attention modules have been proposed to model interdependencies among all instances. However, in this paper we question: Is r...

Infrared small target detection plays an important role in the infrared search and tracking applications. In recent years, deep learning techniques have been introduced to this task achieved noteworthy effects. Following general object segmentation methods, existing methods usually process image from global view. However, locality of targets extreme class-imbalance between background pixels are...

The refined segmentation of nuclei and the cytoplasm is most challenging task in automation cervical cell screening. U-Shape network structure has demonstrated great superiority field biomedical imaging. However, classical U-Net cannot effectively utilize mixed domain information contextual information, fails to achieve satisfactory results this task. To address above problems, a module based o...