Abstract: This paper presents an enhanced approach to real-time object detection, addressing challenges such as movement dynamics and environmental variability. The proposed method employs transfer ...

This project implements a comprehensive Computer Vision MLOps pipeline for aerial object analysis, specifically designed to classify and detect birds vs drones in aerial imagery. The system combines: ...

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 ...

Jo Craig (they/them) is a writer on Game Rant from Scotland and has been in the industry for nearly a decade dissecting comic book movie trailers for hours and diving headfirst into horror. They still ...

Real-time object detection is a critical capability in computer vision, enabling systems to identify and localize objects instantly in dynamic environments. Recent advances leverage optimized ...

Add an Object Detection notebook using any model !! You can add any model , either train it or use pretrained weights for generating best results !! Create proper documentation supporting your choice ...

Although it is well believed for years that modeling relations between objects would help object recognition, there has not been evidence that the idea is working in the deep learning era. All ...