Abstract: Real-time object detection on edge devices operates under tight computational, memory, and power budgets. Prior work typically treats model compression and hardware acceleration ...

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 ...

With the rapid development of marine resource exploitation and the increasing demand for underwater robot inspection, achieving reliable target perception in turbid, low-illumination, and spectrally ...

The broad range of Scolytinae pests sizes and their subtle visual similarities, especially in smaller species, continue to challenge the accuracy of mainstream object detection models. To address ...

ABSTRACT: The study adapts several machine-learning and deep-learning architectures to recognize 63 traditional instruments in weakly labelled, polyphonic audio synthesized from the proprietary Sound ...

Real-time object detection and classification. Paper: version 1, version 2. All input images from default folder sample_img/ are flowed through the net and predictions are put in sample_img/out/. We ...

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 ...

Description This project implements real-time object detection using the Ultralytics YOLO model. It includes a script for performing detection on live camera feeds or video files, saving the annotated ...