Abstract: Object detection is the method of recognizing and finding objects in digital images and video frames. Over the years, object detection techniques have made significant advances driven by ...

Timely and accurate detection of foreign objects is crucial for the safe operation of transmission lines in power grid. Currently, object detection models have more and more parameters and their ...

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: ...

Abstract: Object detection underwater is one of the most important tasks in various applications: marine biology, environ- mental monitoring, and underwater exploration. In this paper, we discuss a ...

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 ...

What if you could teach a computer to recognize a zebra without ever showing it one? Imagine a world where object detection isn’t bound by the limits of endless training data or high-powered hardware.

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 lesions.

Hertz and other agencies are increasingly relying on scanners that use high-res imaging and A.I. to flag even tiny blemishes, and customers aren’t happy. By Gabe Castro-Root The next time you rent a ...