- D-Drone_v2 VS TrafficSignClassifier
- D-Drone_v2 VS uav-detection
- D-Drone_v2 VS SeeAI
- D-Drone_v2 VS samples
- D-Drone_v2 VS Human-pose-estimation
- D-Drone_v2 VS notebooks
- D-Drone_v2 VS Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment
- D-Drone_v2 VS computervision-recipes
- D-Drone_v2 VS Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning
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This project is an aspect of a big project that is called the Self-Driving Car. One of the essential techniques in Self-Driving Car engineering is detecting the Traffic Sign. In this project I have used Deep Learning for recognizing the Traffic Signs.
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Drone / Unmanned Aerial Vehicle (UAV) Detection is a very safety critical project. It takes in Infrared (IR) video streams and detects drones in it with high accuracy.
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notebooks
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
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Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment
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D-Drone_v2 discussion
D-Drone_v2 reviews and mentions
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An ad-hoc idea for defeating the Shahed-136 suicide drone
Visual detection: https://github.com/5a7man/D-Drone_v2
Stats
5a7man/D-Drone_v2 is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
The primary programming language of D-Drone_v2 is Jupyter Notebook.