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35 articles
Explore the advanced AI technologies behind smart pet devices including computer vision, sensor fusion, and predictive analytics that are revolutionizing pet care.
Learn to build a robotic meal prep system that identifies ingredients, plans meals, and controls robot execution - similar to what's being deployed in San Francisco's Tenderloin community.
Learn to build neural networks for object detection similar to Tesla's Full Self-Driving software using TensorFlow and OpenCV.
Learn to build a dual-camera recording system similar to the popular DualShot Recorder app using Python and OpenCV, covering camera synchronization, image merging, and AI-enhanced processing techniques.
Learn to build a basic face recognition system using Python and OpenCV, similar to the technology used by Disneyland. This beginner-friendly tutorial covers face detection, recognition, and visualization.
Google Photos introduces an AI-powered virtual try-on feature that allows users to experiment with outfits from their existing wardrobe. The tool uses computer vision to create digital wardrobes and mix-and-match clothing combinations.
Meta AI's Sapiens2 is a high-resolution human-centric vision model that simultaneously performs pose estimation, segmentation, and 3D geometry reconstruction using a unified architecture. This breakthrough demonstrates advanced multi-task learning in computer vision.
Learn how to set up and use Google DeepMind's Vision Banana model for image segmentation and depth estimation tasks.
Learn to build a basic AI-powered food identification system similar to VisioLab's checkout technology using Python and pre-trained machine learning models.
Learn to build an autonomous drone flight planning system that can analyze field images and generate optimized spray paths without pre-mapped fields.
This article explains how inspection cameras like the Bebird Earsight Plus D39R utilize advanced imaging technology, fiber optics, and AI algorithms to provide unprecedented visual access to previously obscured spaces.
This article explains the technical challenges and AI integration complexities involved in developing smart glasses, showing how Apple's approach reflects the maturation of augmented reality hardware development.
