Recent advances in artificial intelligence (AI) have significantly intensified research in the
geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-based …

Few-shot aerial image object detection aims to rapidly detect object instances of novel
category in aerial images by using few labeled samples. However, due to the complex …

Few-shot segmentation (FSS), which aims to determine specific objects in the query image
given only a handful of densely labeled samples, has received extensive academic attention …

In recent years, few-shot segmentation (FSS) has received widespread attention from
scholars by virtue of its superiority in low-data regimes. Most existing research focuses on …

Weakly supervised object detection (WSOD) trains detectors by only weak labels, aiming to
save the burden of expensive bounding box-level annotations. Most previous efforts …

ABSTRACT Artificial Intelligence (AI) Machine Learning (ML) technologies, particularly Deep
Learning (DL), have demonstrated significant potential in the interpretation of Remote …

An essential need for accurate visual object tracking is to capture better correlations
between the tracking target and the search region. However, the dominant Siamese-based …

Benefiting from advances in few-shot learning techniques, their application to dense
prediction tasks (eg, segmentation) has also made great strides in the past few years …

Recent years have witnessed the astonishing development of transformer-based paradigm
in single object tracking (SOT) in generic videos. However, due to the fact that the targets of …

Most existing adversarial attack methods against detectors involve adding adversarial
perturbations to benign images to synthesize adversarial examples. However, directly …