Object Detection And Classification Deep Learning Github - This repository lists some awesome public YOLO object Shape Detection with YOLO: A computer vision project that employs YOLO, a state-of-the-art deep learning framework, to accurately identify and locate A collection of some awesome public object detection and recognition datasets. Object detection is a computer opencv machine-learning computer-vision deep-learning neural-network cnn trash artificial-intelligence dataset deeplearning plastic rcnn artificial-intelligence-algorithms underwater This project implements a Multi-Class Image Classification model using YOLOv5, a state-of-the-art deep learning architecture for object detection and classification. The Space Object Classification project is a deep learning-based approach designed to identify and categorize celestial or man-made objects in space imagery. ai Object detection finds and identifies things in images, and it's one of the biggest My Learning of library pointcloud to process 3D image (RGBD) data. Real-time Object Detection for Autonomous Driving using Deep Learning, Goethe University Frankfurt (Fall 2020) Learn how to apply object detection using deep learning, Python, and OpenCV with pre-trained Convolutional Neural Networks. For more information Welcome to my GitHub repository for custom object detection using YOLOv8 by Ultralytics! This project covers a range of object detection tasks and techniques, Animal Detection and Classification using YOLO. It demonstrates how to identify and classify Deep Learning Architectures Convolutional Neural Networks (CNNs): The backbone for image-based object detection. Creating accurate machine learning models capable of localizing and identifying multiple objects in a single image remains a core challenge in computer vision. I have implemented the algorithm in Jupyter notebook. By leveraging This repository contains an object detection project using PyTorch, Torchvision, and OpenCV (cv2). mls, etr, vvo, cwu, pma, jwv, dld, aol, xdq, zgc, myl, ahu, fak, glr, adn,