This project is an object detection system that leverages the SSD MobileNet V3 model to detect objects in images and videos. It includes a Python-based API for model inference and a Java-based web ...

This project is a web-based application that utilizes real-time object detection to identify and label objects within an image or video stream. It is built using Next.js, ONNXRuntime, YOLOv7, and ...

Abstract: This research utilizes the YOLOv9c model, an advanced object detection web application, integrating it into a Flask framework. The proposed method involves dataset gathering from users, data ...

There are two necessary parts of this system: a web-based object detection application which is achieved by SSD-MobileNetV2 object detection algorithm, can recognize the objects including persons, ...