Qiao03's Stars
HlEvag/DMCM
The code of the proposed DMCM method will be publicly available here.
huanliu233/MATA
MATA for Hyperspectral Image Classification
YuxiangZhang-BIT/IEEE_TNNLS_Gia-CFSL
Graph Information Aggregation Cross-domain Few-shot Learning for Hyperspectral Image Classification. IEEE TNNLS, 2022.
chenhaoxing/M2L
This repository is the code of paper "Multi-level Metric Learning for Few-shot Image Recognition".(ICANN-2022))
CSer-Tang-hao/BSFA-FSFG
[TCSVT23, Highly Cited Paper] Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignment
plai-group/simple-cnaps
Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)
Frankluox/Channel_Importance_FSL
[ICML 2022] Channel Importance Matters in Few-shot Image Classification
Yussef93/FewShotCellSegmentation
Code of "Few-shot microscopy image cell segmentation " https://link.springer.com/chapter/10.1007/978-3-030-67670-4_9
odegeasslbc/FastGAN-pytorch
Official implementation of the paper "Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis" in ICLR 2021
moukamisama/F2M
icoz69/DeepEMD
Code for paper "DeepEMD: Few-Shot Image Classification with Differentiable Earth Mover's Distance and Structured Classifiers", CVPR2020
kaixin96/PANet
Code for our ICCV 2019 paper PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment
hytseng0509/CrossDomainFewShot
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)
sjliu68/MDL4OW
S. Liu, Q. Shi and L. Zhang, "Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2020.3018879.
97aditi/CFAD
A dimensionality reduction method tailored to high-dimension small-sample size data
atik666/representationTransfer
Unsupervised Representation Learning to Aid Few-Shot Transfer Learning
fhqxa/HFKT
Zhong Zhang,Zhiping Wu, Minjie Hu, Hong Zhao*, Knowledge transfer based hierarchical few-shot learning via tree-structured knowledge graph
hatute/FSTL4HRDR
Source code for "Few-Shot Transfer Learning for Hereditary Retinal Diseases Recognition" (MICCAI 2021)
VITA-Group/DnA
[ECCV 2022] "Improve Few-Shot Transfer Learning with Low-Rank Decompose and Align" by Ziyu Jiang, Tianlong Chen, Xuxi Chen, Yu Cheng, Luowei Zhou, Lu Yuan, Ahmed Awadallah, Zhangyang Wang
ZhongjieYu/TransMatch_code
Pytorch code for our paper TransMatch: a transfer learning scheme for semi-supervised few-shot learning
AliBahri94/Remote-Sensing-Image-Classification-via-Improved-Cross-Entropy-Loss-and-Transfer-Learning-Strategy
Remote Sensing Image Classification via Improved Cross-Entropy Loss and Transfer Learning Strategy Based on Deep Convolutional Neural Networks
phikun/LAI-Inversion
Assignment: Inverting Leaf Area Index (LAI) with MODIS data and ProSAIL model
yanghuikang/Landsat-LAI
Employing a data-driven approach to generate Leaf Area Index (LAI) maps from Landsat images over CONUS
ostojanovic/bayesian_lai
Code repository for the paper "Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets"
mjan2021/Dermoscopic-image-classification
Repository contain code for paper titled "Class Imbalanced Dermoscopic Image Classification using Data Augmentation and GAN"
yc-cui/Extend-GAN
[GRSL 2024] Reconstruction of Large-Scale Missing Data in Remote Sensing Images Using Extend-GAN
MachineLP/train_arch
cnn+rnn+attention: vgg(vgg16,vgg19)+rnn(LSTM, GRU)+attention, resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152)+rnnrnn(LSTM, GRU)+attention, inception_v4+rnn(LSTM, GRU)+attention, inception_resnet_v2+rnn(LSTM, GRU)+attention,..... vgg(vgg16,vgg19), resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152), inception_v4, inception_resnet_v2,.....
weihancug/GAN-based-HRRS-Sample-Generation-for-Image-Classification
The GAN-based method is used to generate high-resolution remote sensing for data augmentation and image classification.