Seamlessly integrate LLMs into scikit-learn.

Supercon2: Automatic extraction of materials and properties from superconductor scientific literature

Generative deep learning model for inorganic materials

Language model for materials composition generation

GAN for generating chemical compositions

Grobid module for superconductor material and properties extraction

Superconductors material dataset

Crack Detection On Highway Or Pavement Using OpenCV

Detects cracks in real time

Real time crack segmentation using PyTorch, OpenCV and ONNX runtime

SnapCrack is an Android application and web UI that is capable of crack detection and localization in real time. SnapCrack leverages basic object detection algorithms to detect cracks in real-time.…

A pre-trained MobileNet model for detecting cracks on concrete structures

This is a Surface Crack Detection project implemented with the Tensorflow. We fine tuning some deep learning models (like VGG 19, VGG16, MobileNetV2, ...). Use Surface Crack Detection dataset avail…

A pre-trained MobileNet model for detecting cracks on concrete structures.

Composition-based predictions for chemically novel, high-temperature superconductors.

An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]

Encode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such as Palette.