The inherent noisy and sparse characteristics of radar data pose challenges in finding effective representations for 3D object detection. In this paper, we propose RadarDistill, a novel knowledge ...

BoltzFormer is designed for text promptable segmentation, with superior performance for small objects. It performs Boltzmann sampling within the attention mechanism in the transformer, allowing the ...

Brain tumors pose a critical threat to human health, and early detection is essential for improving patient outcomes. This study presents two key enhancements to the YOLOv11 architecture aimed at ...

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 ...

Abstract: In RGB-infrared aerial image object detection, fully utilizing the advantages of both RGB and infrared images for effective detection is a key challenge in this field. In response to the ...

Abstract: Detecting tiny objects in remote sensing images has been an intriguing yet challenging topic in remote sensing image processing. While significant progress has been made in many studies, ...