Abstract: In the field of remote sensing image processing, remote sensing image object detection is a crucial undertaking. However, the existing object detection algorithms have a considerable number ...
S3OD is a large-scale fully synthetic dataset for salient object detection and background removal, with 140K high-quality images generated using diffusion models. Our model, trained on large-scale ...
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 ...
Introduction: Accurate vehicle analysis from aerial imagery has become increasingly vital for emerging technologies and public service applications such as intelligent traffic management, urban ...
Objective: To enhance the automatic detection precision of diabetic retinopathy (DR) lesions, this study introduces an improved YOLOv8 model specifically designed for the precise identification of DR ...
Abstract: Accurate and efficient small object detection using multimodal remote sensing images on resource-constrained aerial platforms is a challenging task. Most existing solutions rely on complex ...
This project implements real-time object detection using OpenCV and a pre-trained SSD MobileNet V3 model. The application can identify and label various objects from a webcam feed or uploaded images ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback