IEEE

SFBDA: A Semantic-Decoupled Data Augmentation Framework for Infrared Few-Shot Object Detection on UAVs

Abstract: Few-shot object detection (FSOD) is a critical frontier in computer vision research. However, the task of an infrared (IR) FSOD presents significant technical challenges, primarily due to ...
GitHub

UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection

The official implementation for "UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection". The detection of ligand binding sites for proteins is ...
GitHub

InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition

InstructSAM is a training-free framework for Instruction-Oriented Object Counting, Detection, and Segmentation (InstructCDS). We construct EarthInstruct, an InstructCDS benchmark for remote sensing.
Frontiers

MOSSNet: multiscale and oriented sorghum spike detection and counting in UAV images

Background: Accurate sorghum spike detection is critical for monitoring growth conditions, accurately predicting yield, and ensuring food security. Deep learning models have improved the accuracy of ...
IEEE

MV-YOLO: An Efficient Small Object Detection Framework Based on Mamba

Abstract: Small-object detection in uncrewed aerial vehicle (UAV) and remote-sensing imagery remains challenging because targets occupy only a few pixels, features are sparse, objects are often ...