How to Train U-NET in Google Colab: A Step-by-Step Guide
Are you looking to train U-NET for semantic segmentation, background removal, or salient feature highlighting in Google Colab? This step-by-step guide from Augmented Startups will walk you through the entire process, from setting up the environment to loading and training your own dataset
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Raspberry pi YOLOv4-tiny Object Detection with Intel Neural Compute Stick and openVINO
Here’s an interesting computer vision project. I really need to unpack more of my stuff so I can find my Raspberry Pis.
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The Intelligent Edge by Microsoft
Watch Paul de Carlo, Microsoft Cloud Developer Advocate, step through his Intelligent Edge Hands-on Lab (https://aka.ms/iotshow/intelligentedge — which is open source and available for you to try) During this lab, Paul deploys an IoT Edge module to an NVIDIA Jetson Nano development board to allow for detection of objects from the live video stream of […]
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How Computers Learn to Recognize Objects
Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible. Today, computer vision systems do it with greater than 99 percent accuracy. How? Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can […]
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Windows Machine Learning: Models and Features
Killian and Rosane along with guest star Rufus the robot! discuss loading models and understanding how to determine a given model’s expected inputs and output features. For more information about Windows ML check out https://aka.ms/OverviewOfWinML
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Object Detection YOLO Style
Siraj Raval takes on YOLO. It’s not what you think. This time it stands for You Only Look Once, a great object detection method for adding computer vision features to live streaming video.
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