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Learn to segment microscope images using histogram-based thresholding in Python with DigitalSreeni. Master basic image processing operations in under an hour.
Learn to denoise microscope images using Python in less than an hour with DigitalSreeni. Master denoising algorithms from Sciki-image and numpy libraries. Code included.
Learn to analyze scratch assays using Python in less than an hour with DigitalSreeni. Master entropy filter, Otsu thresholding, and image processing techniques.
Learn image processing using scikit-image in Python with DigitalSreeni. Master resizing, reshaping, edge detection, and segmentation in under an hour.
Learn to manipulate and process images using Python's Pillow library with DigitalSreeni. Master resizing, cropping, and more in under an hour.
Learn to read images in Python using popular libraries in less than an hour with DigitalSreeni. Understand non-standard image reading and access the code on GitHub.
Learn to denoise 2D and 3D multichannel scientific images using Noise2Void deep learning approach in less than an hour with DigitalSreeni.
Learn the basics of data science, machine learning, and deep learning with DigitalSreeni in under an hour. Understand the differences and benefits, and structure your learning plan.
Learn to process whole slide images using openslide in less than an hour with DigitalSreeni. Extract, normalize, and save processed images separately. Code included.
Learn to label images for semantic segmentation using Label Studio in less than an hour with DigitalSreeni. Includes creating projects and exporting annotations.
Learn semi-supervised learning with generative adversarial networks in less than an hour with DigitalSreeni. Ideal for handling large, partially labeled datasets, enhancing accuracy.
Learn semi-supervised learning with generative adversarial networks (GANs) in under an hour with DigitalSreeni. Enhance your skills in training models on partially labeled images for improved accuracy.
Explore Single Image Super-Resolution using SRGAN with DigitalSreeni. Understand key concepts in under an hour by studying the original publication.
Learn Pix2Pix GAN for image translation in under an hour with DigitalSreeni. Understand key concepts, generator and discriminator architecture, and apply it to satellite images and scientific visuals.
Learn to use autoencoders for image reconstruction and visualize feature responses in deep learning models with DigitalSreeni. Less than 1-hour workload.
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