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Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Code release for "Masked-attention Mask Transformer for Universal Image Segmentation"
PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.
这是一个deeplabv3-plus-pytorch的源码，可以用于训练自己的模型。
Datasets, Transforms and Models specific to Computer Vision
deep learning for image processing including classification and object-detection etc.
mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).
README and scripts for the Cityscapes Dataset
Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
YLearn, a pun of "learn why", is a python package for causal inference
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
LibCity: An Open Library for Urban Spatial-temporal Data Mining
Cryptocurrency trading bot with a graphical user interface with support for simulations, backtests, optimizations, and running live bots.
Sequence modeling benchmarks and temporal convolutional networks
This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.
Gated Channel Transformation for Visual Recognition (CVPR 2020)
A novel spatio-temporal adaptive graph convolutional network model (STAGCN) based on deep learning
Source code of implementing spatial-temporal zero-inflated negative binomial network for trip demand prediction
[PAKDD 2021] SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network
Official PyTorch implementation of "Cross-Node Federated Graph Neural Network for Spatio-Temporal Modeling".
IJCNN2021 paper by Eric L. Manibardo. Python code and datasets.
MAGCN: A Multi-Adaptive Graph Convolutional Network for Traffic Forecasting