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Learn Image Segmentation, earn certificates with free online courses from Stanford, UC Berkeley, Columbia University, Duke and other top universities around the world. Read reviews to decide if a class is right for you.
Understand the basics of image analysis and learn how to collect, manipulate, and analyse data from images for plant phenotyping.
Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.
Learn how computer vision is important in AI and gain practical experience of image analysis.
Master Tensorflow Object Detection with this 1-2 hour program. Learn to set up TFOD with Tensorflow 2.0, install necessary tools, and perform real-time image segmentation and object detection.
Learn cutting-edge deep learning techniques with Jeremy Howard in 15 hours, covering object detection, NLP, neural translation, GANs, and image enhancement.
Learn practical image processing workflows in MATLAB
Explore uNet and BodyPix with ml5.js in this 2-3 hour material from Coding Train, featuring hands-on challenges and community contributions.
Learn to use Python, OpenCV, and BodyPix model for real-time body segmentation and background removal in less than an hour with Nicholas Renotte.
Learn to implement U-NET for semantic image segmentation from scratch in less than an hour with Aladdin Persson. Includes training setup and evaluation.
Learn to train the Mask R-CNN detector for image segmentation using a free online GPU with Pysource. Understand object identification and polygon drawing in under an hour.
Explore the latest advancements in ConvNets with Aleksa Gordić's concise guide, covering new design ideas, training procedures, and their application in computer vision.
Learn to use Random Walker segmentation in Python for image processing with DigitalSreeni. Master the technique in under an hour using a noisy BSE image from an alloy.
Learn to segment microscope images using histogram-based thresholding in Python with DigitalSreeni. Master basic image processing operations in under an hour.
Learn to apply 3D U-Net for semantic segmentation on volumes from FIB-SEM, CT, MRI, etc. in less than an hour with DigitalSreeni.
Boost your U-Net semantic segmentation performance with DigitalSreeni's guide to ensemble multiple trained networks like ResNet34, Inception V3, and VGG16 in under an hour.
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