Udemy - AI Hand Gesture and Traffic Sign Detection with Python an...
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Last checked: Jun. 24th '25
Date uploaded: Jun. 24th '25
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AI Hand Gesture & Traffic Sign Detection with Python & CV
https://WebToolTip.com
Published 5/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 3m | Size: 733 MB
Real-Time Hand Gesture & Traffic Sign Detection with Python, OpenCV & Deep Learning
What you'll learn
Learn hand gesture and traffic sign recognition for HCI, accessibility, road safety, and autonomous systems.
Set up Python with OpenCV, MediaPipe, TensorFlow for real-time gesture and sign recognition.
Explore gesture and traffic sign detection for control systems, virtual interfaces, and smart transportation.
Detect hand gestures using MediaPipe and classify signs using EfficientNet B0 in real-time.
Recognize gestures like Thumbs Up, Victory, Fist, and classify traffic signs with ML and landmarks.
Preprocess images and videos using resizing, normalization, and augmentation for better model input.
Visualize results with labels, confidence scores, and bounding boxes for easy interpretation.
Train EfficientNet B0 on traffic signs and optimize hyperparameters to improve accuracy.
Handle issues like lighting, occlusions, and low resolution for robust real-world performance.
Use gesture recognition for control, gaming, and accessibility; use sign detection for driving and safety.
Integrate both systems into real-time apps for smart interaction and decision-making.
Requirements
Basic understanding of Python programming (helpful but not mandatory).
A laptop or desktop computer with internet access[Windows OS with Minimum 4GB of RAM).
No prior knowledge of AI or Machine Learning is required—this course is beginner-friendly.
Enthusiasm to learn and build practical projects using AI and IoT tools.
https://WebToolTip.com
Published 5/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 3m | Size: 733 MB
Real-Time Hand Gesture & Traffic Sign Detection with Python, OpenCV & Deep Learning
What you'll learn
Learn hand gesture and traffic sign recognition for HCI, accessibility, road safety, and autonomous systems.
Set up Python with OpenCV, MediaPipe, TensorFlow for real-time gesture and sign recognition.
Explore gesture and traffic sign detection for control systems, virtual interfaces, and smart transportation.
Detect hand gestures using MediaPipe and classify signs using EfficientNet B0 in real-time.
Recognize gestures like Thumbs Up, Victory, Fist, and classify traffic signs with ML and landmarks.
Preprocess images and videos using resizing, normalization, and augmentation for better model input.
Visualize results with labels, confidence scores, and bounding boxes for easy interpretation.
Train EfficientNet B0 on traffic signs and optimize hyperparameters to improve accuracy.
Handle issues like lighting, occlusions, and low resolution for robust real-world performance.
Use gesture recognition for control, gaming, and accessibility; use sign detection for driving and safety.
Integrate both systems into real-time apps for smart interaction and decision-making.
Requirements
Basic understanding of Python programming (helpful but not mandatory).
A laptop or desktop computer with internet access[Windows OS with Minimum 4GB of RAM).
No prior knowledge of AI or Machine Learning is required—this course is beginner-friendly.
Enthusiasm to learn and build practical projects using AI and IoT tools.