Pinned Repositories
academic-kickstart
ALMM_TIP
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing, IEEE TIP, 2019.
autoencoders
Implementation of several different types of autoencoders
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
BOT-Learning
CNN-AL-MRF
This is the code of "Hyperspectral Image Classification with Convolutional Neural Network and Active Learning".
deepcluster
Deep Clustering for Unsupervised Learning of Visual Features
ExViT
HyperSpectralToolbox
HyperSpectral Matlab Toolbox forked from Sourceforge
UCSL
jingyao16's Repositories
jingyao16/ExViT
jingyao16/UCSL
jingyao16/deepcluster
Deep Clustering for Unsupervised Learning of Visual Features
jingyao16/academic-kickstart
jingyao16/ALMM_TIP
An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing, IEEE TIP, 2019.
jingyao16/awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
jingyao16/CNN-AL-MRF
This is the code of "Hyperspectral Image Classification with Convolutional Neural Network and Active Learning".
jingyao16/Codes_SpectralFormer
jingyao16/dgconv.pytorch
[ICCV 2019] PyTorch implementation of Dynamic Grouping Convolution and Groupable ConvNet with pre-trained G-ResNeXt models
jingyao16/ECCV2018_J-Play
Danfeng Hong, Naoto Yokoya, Jian Xu, Xiaoxiang Zhu. Joint & Progressive Learning from High-Dimensional Data for Multi-Label Classification, ECCV, 2018.
jingyao16/ECCV2020_CUCaNet
Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution, ECCV, 2020. (PyTorch)
jingyao16/euler
A distributed graph deep learning framework.
jingyao16/gcn
Implementation of Graph Convolutional Networks in TensorFlow
jingyao16/HyFTech-Hyperspectral-Shallow-Deep-Feature-Extraction-Toolbox
This Toolbox includes Hyperspectral Feature Extraction Techniques including Unsupervised, Supervised, and Deep Feature Extraction
jingyao16/IEEE_JSTARS_RLML
Danfeng Hong, Naoto Yokoya, Xiaoxiang Zhu. Learning a Robust Local Manifold Representation for Hyperspectral Dimensionality Reduction, IEEE JSTARS, 2017.
jingyao16/IEEE_TGRS_AIPs
Danfeng Hong, Xin Wu, Pedram Ghamisi, Jocelyn Chanussot, Naoto Yokoya, Xiaoxiang Zhu. Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification, IEEE TGRS, 2020, 58(6): 3791-3808.
jingyao16/IEEE_TGRS_CoSpace
Danfeng Hong, Naoto Yokoya, Jocelyn Chanussot, Xiaoxiang Zhu. CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences, IEEE TGRS, 2019.
jingyao16/IEEE_TGRS_GCN
Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Graph Convolutional Networks for Hyperspectral Image Classification, IEEE TGRS, 2020.
jingyao16/IEEE_TGRS_J-SLoL
Lianru Gao, Danfeng Hong, Jing Yao, Bing Zhang, Paolo Gamba, Jocelyn Chanussot. Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning, IEEE TGRS, 2020.
jingyao16/IguanaTexMac
IguanaTex for mac
jingyao16/ISPRS_LeMA
Danfeng Hong, Naoto Yokoya, Nan Ge, Jocelyn Chanussot, Xiaoxiang Zhu. Learnable Manifold Alignment (LeMA): A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification, ISPRS JP&RS, 2019.
jingyao16/ladder_network_keras
Semi-Supervised Learning with Ladder Networks in Keras. Get 98% test accuracy on MNIST with just 100 labeled examples !
jingyao16/LDS-GNN
Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
jingyao16/MHF-net
Code of Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
jingyao16/spektral
Graph Neural Networks with Keras and Tensorflow 2.
jingyao16/sporco
Sparse Optimisation Research Code
jingyao16/Truncated-Loss
PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018
jingyao16/uda
Unsupervised Data Augmentation (UDA)
jingyao16/USRNet
(CVPR, 2020) (PyTorch)
jingyao16/WWW20-Hands-on-Tutorial
Materials for DGL hands-on tutorial in WWW 2020