Abstract: This study develops a scalable, effective, and user-friendly solution to tackle the problem of real-time object detection in photos. The suggested approach ...

This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...

I tried using DINOv3 as the pre-trained model for the detector and encountered an issue. When defining the Transformer, self.reference_points（not two-stage） is initialized as follows: if two_stage: ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

Small object detection is a critical task in applications like autonomous driving and ship black smoke detection. While Deformable DETR has advanced small object detection, it faces limitations due to ...

What made the pulses puzzling to the astronomers was that they came in the form of both radio waves and X-rays. The discovery marks the first time that such objects, called long-period transients, ...

Abstract: Deep learning-based object detection research has primarily evolved around RGB camera imagery. While state-of-the-art models like YOLO, SSD, and RetinaNet demonstrate high accuracy in RGB ...