YOLO AI technology page Top Builders

Explore the top contributors showcasing the highest number of YOLO AI technology page app submissions within our community.

YOLO

YOLO (You Only Look Once) is a state-of-the-art, real-time object detection algorithm that can quickly detect and locate objects within an image or video. The YOLO architecture works by taking an input and separating it into a grid of cells and each of these cells is in charge of detecting objects within that region. YOLO returns the bounding boxes containing all the objects in the image and predicts the probability of an object being in each of the boxes and also predicts a class probability to help identify the type of object it is. YOLO is a highly effective object detection algorithm and making YOLO and open-source project led the community to make several improvements in such a limited time.

General
Relese date	2015
Author	Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi
Paper	(https://arxiv.org/abs/1506.02640)
Type	Object detection algorithm

YOLO - Resources

Learn even more about YOLO!

v7 Labs Blog "YOLO: Algorithm for Object Detection Explained".
YOLOv5 Repository Object detection architectures and models pretrained on the COCO dataset.
YOLOv6 Web demo Gradio demo for YOLOv6 for object detection on videos.
Hugging Face Spaces Test YOLOv7 in the browser with Hugging Face Spaces.

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YOLO AI technology page Hackathon projects

Discover innovative solutions crafted with YOLO AI technology page, developed by our community members during our engaging hackathons.

DietDeep AI-Powered Nutrition Guide

DietDeep is an AI-powered meal planner that personalizes dietary recommendations based on user goals and meal images. It utilizes DeepSeek-R1 for meal plan generation, a pretrained YOLOv10 model for food classification, and the USDA API for nutrition data. Users enter dietary goals, upload meal images, and receive customized meal plans with portion sizes and nutritional values. The system intelligently combines detected food items with nutritional data to create well-balanced meals. Built with Streamlit for an interactive UI, DietDeep aims to simplify healthy eating using AI, making personalized nutrition accessible and efficient for individuals with diverse dietary needs.

AstroCleanAI -- AI-Powered Space Agent

AstroCleanAI is an advanced AI-powered space debris tracking and risk prediction system designed to enhance space safety. With the increasing amount of space junk threatening satellites and future missions, managing debris is more critical than ever. AstroCleanAI leverages artificial intelligence to detect, classify, and predict debris behavior, ensuring proactive collision avoidance and efficient satellite operations. 🛰️ Key Features: Real-Time Space Debris Detection & Classification – Uses deep learning models (YOLOv5, ResNet-50) to analyze satellite imagery and radar data, identifying debris based on size, trajectory, and risk level. AI-Powered Collision Risk Prediction – Implements an XGBoost-based risk assessment model to predict satellite-debris collision probabilities and suggest optimal avoidance maneuvers. Interactive Space Debris Simulation – Visualizes real-world debris movement and potential collision risks using 3D orbital mechanics modeling. Public Engagement Dashboard – Allows researchers, students, and enthusiasts to explore real-time space debris tracking and AI-driven insights. 🛠️ Technology Stack: AI & Machine Learning: TensorFlow, PyTorch, YOLOv5, ResNet-50, XGBoost Space Data & Analysis: NASA’s Open TLE Data, OpenCV for satellite imagery processing Web & Visualization: Streamlit, Matplotlib (3D trajectory simulation), Flask backend 🌍 Impact & Future Scope: AstroCleanAI contributes to sustainable space exploration by mitigating debris-related risks, preventing costly satellite damage, and optimizing space traffic management. Future enhancements may include integrating real-world satellite telemetry, collaborating with space agencies for improved predictions, and developing an autonomous debris mitigation system capable of orchestrating deorbiting maneuvers.

UrbanGrid

Urban Navigators is an innovative traffic management system leveraging AI and advanced computer vision models to revolutionize urban traffic management. The platform consists of two panels: Admin Panel: A comprehensive dashboard providing insights into active accidents, traffic analytics, signal control for specific regions, e-challan management, and emergency response coordination. AI models like YOLOv11 enable accident detection, license plate recognition, and dynamic traffic signal adjustments based on vehicle count, offering real-time operational efficiency. User Panel: Provides traffic updates through an interactive map, accident reporting capabilities, e-challan information with payment options, and a traffic updates section for better route planning. The system includes three operational modes—Normal, AI Mode, and Night Mode—to adapt to different traffic conditions. This hackathon project showcases the potential of AI to enhance urban mobility, reduce congestion, and improve road safety.

BlindNav

BlindNav is a navigation aid tailored for visually impaired individuals, combining state-of-the-art AI models for seamless interaction. By leveraging YOLOv10 for object detection and tracking, the app identifies both static and dynamic objects in real-time. Whisper captures voice input from users, while O1 generates context-aware, concise responses to user questions about their surroundings. Users can upload or capture images, and the app processes them to give auditory feedback based on object tracking results. BlindNav aims to provide an intuitive and practical navigation solution for visually impaired users, improving their independence and situational awareness.

MyVision

My Vision is an AI-powered app designed to assist visually impaired individuals by making their surroundings more accessible. With over 285 million people worldwide affected by visual impairment, My Vision offers a simple solution: users take a picture, ask a question, and receive an instant spoken description of their environment. This real-time feedback helps users navigate and interact with the world around them. Beyond supporting the visually impaired, My Vision includes features like Optical Character Recognition (OCR) for real-time translation, making it useful for everyone. What makes My Vision unique is its context-aware results, support for various environments, and Episodic Memory, which remembers repeated objects or settings to enhance user experience and independence.

Diet Vision

Long gone are the days where we must manually record what we ate and calculate how much proteins, fats, calories, and carbs we ate. Diet Vision is a small pin/necklace that automatically takes pictures when you take your second bite of food. It utilizes Nvidia's computer vision to analyze what pictures you ate, what exactly is in the food, how much is in each meal, and what food you should eat to reach your daily calorie goals. It utilizes low energy bluetooth and interfaces with the Libre 2 CGM, which is used by millions annually. You can also adjust the nutrient facts about each meal so it continuously learns using Inceptionv3 model!