Embedded systems projects focus on designing and implementing specialized computing solutions into devices for specific applications.
We walk through how contrastive learning enhances ML models by learning differences and similarities in data.
Explore how computer vision infrastructure assists in the development and improvement of renewable energy and resources.
Learn how monocular depth estimation works, and follow a step-by-step tutorial to build your own depth estimation model.
TensorFlow Lite is a lightweight machine learning library to power real-time computer vision with edge devices to solve real-world problems.
Guide to CVAT, the computer vision annotation tool. The best features, advantages, and limitations you need to know.
Modern Image Classification in Computer Vision: How Machine Learning and Neural Networks drive the performance of Image Classification.
The OpenPose library uses neural networks to perform real-time human body pose estimation for single- and multi-person video analysis.
YOLOv11, released in Oct 2024, provides high processing power, efficiency, and compatibility for cloud and edge devices.
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