In the realm of semi-supervised graph learning, pseudo-labeling is a pivotal strategy to
utilize both labeled and unlabeled nodes for model training. Currently, confidence score is …

Few-shot learning brings the machine close to human thinking which enables fast learning
with limited samples. Recent work considers local features to achieve contextual semantic …

The goal of click-through rate (CTR) prediction in recommender systems is to effectively
work with input features. However, existing CTR prediction models face three main issues …

Water-related optics images are often degraded by absorption and scattering effects.
Current underwater image enhancement (UIE) methods improve image quality but neglect …

Existing Camouflaged Object Detection (COD) methods rely heavily on large-scale pixel-
annotated training sets, which are both time-consuming and labor-intensive. Although …

In hyperspectral image classification (HSIC), every pixel of the HSI is assigned to a land
cover category. While convolutional neural network (CNN)-based methods for HSIC have …

Research on wildlife monitoring methods is a crucial tool for the conservation of rare wildlife
in China. However, the fact that rare wildlife monitoring images in field scenes are easily …

Infrared small target detection involves determining the coordinate position of the target in
complex infrared images. However, challenges arise due to the absence of internal texture …

Synthetic aperture radar (SAR) can detect moving targets on the ground/sea, and
highresolution imaging on the ground/sea has critical applications in both military and …

Recent advancements in simultaneous localization and mapping (SLAM) have significantly
improved the handling of dynamic objects. Traditionally, SLAM systems mitigate the impact …