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PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译，支持 Google/DeepL/Ollama/OpenAI 等服务，提供 CLI/GUI/Docker/Zotero
Open source Windows Application in Python for Geosciences, Artificial Intelligence and Data Sciences - Initial stages, 2021
Framework for computing seismic attributes with Python.
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Simple static web-based mask drawer, supporting semantic segmentation and video segmentation with interactive Segment Anything Model 2 (SAM2).
Collection of notebooks showcasing how to use various PyLops functionalities
Fast approximate simulation of seismic waves using WaveNet
Deep learning dataset and benchmark for first-break detection from hardrock seismic reflection data
The best free and open-source automated time tracker. Cross-platform, extensible, privacy-focused.
Neural network-based CO2 interpretation for 4D Sleipner seismic images
OpenChat: Advancing Open-source Language Models with Imperfect Data
PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
FC-DenseNet in PyTorch for Semantic Segmentation
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, Cont…
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
This Repository is implementation of majority of Semantic Segmentation Loss Functions
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
DiceLoss for PyTorch, both binary and multi-class.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Translate PDF, EPub, webpage, metadata, annotations, notes to the target language. Support 20+ translate services.
A PyTorch implementation of EfficientNet