Electrolytes have recently regained significant attention in rechargeable batteries due to the
discovery that the electrolyte microstructures play a determinant role in battery performance …

Practical applications ask for object detection models that achieve high performance at low
overhead. Knowledge distillation demonstrates favorable potential in this case by …

Fine-grained oriented object recognition (FGO) is a practical need for intellectually
interpreting remote sensing images. It aims at realizing fine-grained classification and …

Current mainstream object detection methods for large aerial images usually divide large
images into patches and then exhaustively detect the objects of interest on all patches, no …

Weakly supervised object detection in remote sensing images (RSI) is still a challenge
because of the lack of instance-level labels, and many existing methods have two problems …

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 …

Effective feature fusion of multispectral images plays a crucial role in multispectral object
detection. Previous studies have demonstrated the effectiveness of feature fusion using …

Advanced patch attacks (PAs) on object detection in natural images have pointed out the
great safety vulnerability in methods based on deep neural networks (DNNs). However, little …

Diffusion models have demonstrated exceptional efficacy in various generative applications.
While existing models focus on minimizing a weighted sum of denoising score matching …

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 …