Shengliang Pu's starred repositories
scikit-learn
scikit-learn: machine learning in Python
mmdetection
OpenMMLab Detection Toolbox and Benchmark
segmentation_models.pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
segmentation_models
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
awesome-slam-datasets
A curated list of awesome datasets for SLAM
thundersvm
ThunderSVM: A Fast SVM Library on GPUs and CPUs
thundergbm
ThunderGBM: Fast GBDTs and Random Forests on GPUs
OctaveConv_pytorch
Pytorch implementation of newly added convolution
OctaveConv
A MXNet Implementation for Drop an Octave
deepaugment
Discover augmentation strategies tailored for your dataset
cellularAutomata
a collection of cellular automata written in Haskell with Diagrams
VisDrone2018-DET-toolkit
Object Detection in Images toolkit for VisDrone2019
EarthMapper
Pipeline for the Semantic Segmentation (i.e., classification) of Remote Sensing Imagery
shogun-data
The Shogun Machine Learning Toolbox (Data Sets)
urban-lu-model
A land use model based on Cellular Automata and Agent-based modelling.
shogun-tutorial
Shogun Tutorial
Low-Power-and-High-Speed-Deep-FPGA-Inference-Engines-for-Weed-Classification
IEEE Access: Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge
shogun-kaggle
Shogun applied to Kaggle tasks
shogun-gpl
Optional GPL compatible parts of Shogun