☁️ Build multimodal AI applications with cloud-native stack
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☁️ Build multimodal AI applications with cloud-native stack
PyTorch code and models for the DINOv2 self-supervised learning method.
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
Caffe models in TensorFlow
Python implementations of the Boruta all-relevant feature selection method.
A clinical decision-evidence benchmark: pull the one fact an answer rests on, and see whether the assistant's action moves with the evidence. Built on HealthBench.
QuadriFlow: A Scalable and Robust Method for Quadrangulation
Android Input Method Editor (IME) based on Whisper
LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation
a generic C++ library for image analysis
ilastik-shell, applets, and workflows to string them together.
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
Bot18 is a high-frequency cryptocurrency trading bot developed by Zenbot creator @carlos8f
🎯 ML-based positioning method from mmWave transmissions - with high accuracy and energy efficiency
A TensorFlow implementation of the Mnemonic Descent Method.
A platform independent tensor library with autograd for the JVM
Ultra high-performance secp256k1 ECC engine | Python, Node.js, Rust, Go, C#, Swift, Java bindings | CUDA, Metal, OpenCL GPU | ECDSA, Schnorr, FROST, MuSig2, BIP-352 | 15+ platforms
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
HistoClean is a tool for the preprocessing and augmentation of images used in deep learning models. This easy to use application brings together the most popular image processing packages from across the python universe, meaning no more looking at documentation! HistoClean provides real time feedback to augmentations and preprocessing options. This allows users to evaluate their steps before implementation.
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
A column-oriented approach to feature engineering. Feature engineering and machine learning: together at last!