As an important pillar of underwater intelligence, Marine Animal Segmentation (MAS) involves segmenting ani-mals within marine environments. Previous methods don't excel in extracting long-range contextual features and over-look the connectivity between discrete pixels. Recently, Segment Anything Model (SAM) offers a universal frame-workfor general segmentation tasks. Unfortunately, trained with n...Show More
In the remote sensing field, change detection (CD) aims to identify and localize the changed regions from dual-phase images over the same places. Recently, it has achieved great progress with the advances of deep learning. However, current methods generally deliver incomplete CD regions and irregular CD boundaries due to the limited representation ability of the extracted visual features. To relie...Show More
Recently, deep learning-based architectures have delivered their great effectiveness in change detection (CD) of remote sensing (RS) images. However, most previous methods are lacking of extracting the multi-scale and long-range information due to the limitation of convolutional operations. To tackle these problems, in this work we propose a fresh framework named Siamese Attentive Convolutional Ne...Show More
