DEIMv2 is an evolution of the DEIM framework while leveraging the rich features from DINOv3. Our method is designed with various model sizes, from an ultra-light version up to S, M, L, and X, to be ...
Abstract: Although great progress has been made in Camouflaged Object Detection (COD), it still faces challenges in complex real-world scenes. Existing methods are primarily designed for visible ...
Abstract: Although existing camouflaged object detection (COD) approaches have developed various strategies to improve performance, there remains plenty of room for further improvement. The primary ...
Background: Accurately diagnosing central nervous system (CNS) infections remains challenging. This study aimed to evaluate the effectiveness of metagenomic next-generation sequencing (mNGS) in ...
This study introduces a small apple pre-thinning dataset designed to support the development of intelligent thinning systems by providing reliable data for small apple detection. The dataset comprises ...