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Johns Hopkins University
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- https://prabhasahiti.github.io/
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Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Local Binary Patterns implementation using Python3 and OpenCV
Local Energy based Shape Histogram (LESH) feature descriptor code
FSL-Mate: A collection of resources for few-shot learning (FSL).
Creating extended depth-of-field image through focus stacking
Reference management solution using Python and Notion.
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
🔊 A comprehensive list of open-source datasets for voice and sound computing (95+ datasets).
Export all clippings from your Kindle device to a database in Notion.
Official repository of the AWS EC2 FPGA Hardware and Software Development Kit
Preparing for machine learning interviews
Python package for graph statistics
Heart murmur detection/analysis from phonocardiogram recordings using Matlab/Octave
📄 🤖 Semantic search and workflows for medical/scientific papers
The personal knowledge management (PKM) tool that grows as you do!
Tangible and Practical Deep Learning Projects Repository for Healthcare such as Cancer, Drug Discovery, Genomic and More
Curated list of awesome open source healthcare software, libraries, tools and resources.
Julia package for reading and writing DICOM (Digital Imaging and Communications in Medicine) files
A simple Python script to automatically render the system color display to greyscale from 10PM to 7 AM. Meant for devices running on Windows OS. Inspired by the Grayscale feature of Google's Digita…
Aggressively forces you to take breaks every x minutes (inspired by TakeABreak for Linux) | Cross-platform
buildfreak93 / openDR
Forked from derbedhruv/openDROpen Source Portable Retina Imaging Device, integrated with cloud-based Deep Learning classifier.
This repo has some usefull links to websites for topics, please fork add and generate a pull-request to join the party
Wall Lab EMG data analysis MatLab to go with FEED data