wh1046403985

metro_prediction

上海地铁预测可视化

transferlearning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

ADAN

An adversarial domain adaptation network to stabilize a fixed Brain-Machine Interface against gradual changes in the recorded neural signals.

SEN-DAL

Multi-modal Physiological Signals based Squeeze-and-Excitation Network with Domain Adversarial Learning for Sleep Staging

CrossDomainFewShot

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)

Code

Adversarial AI applied to cross-user inter-domain and intra-domain adaptation in human activity recognition using wireless signals

DAFOSNET

Official Implementation of "Domain Adaptive Few-Shot Open-Set Learning" in IEEE/CVF International Conference on Computer Vision (ICCV'23)

SigDA

[Pytorch] Code for Paper “SigDA: A Superimposed Domain Adaptation Framework for Automatic Modulation Classification”

MetaModulation

MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks (ICML 2023)

semi-supervised-learning-pytorch

Several SSL methods (Pi model, Mean Teacher) are implemented in pytorch

DualStudent

Code for Paper ''Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning'' [ICCV 2019]

CRCN-AT

SA2SEI

SemiAMR

Open-set-domain-adaptation

Open set domain adaptation code DAOD

mod_dataset

Dataset for 《Dual Residual Denoising Autoencoder for Modulation Signals with Channel Attention Mechanism》

Activation-Functions

AUTOMATIC-MODULATION-CLASSIFICATION

RUBUST DEEP LEARNING-BASED ALGORITHM FOR AUTOMATIC MODULATION CLASSIFICATION

Automatic-Modulation-Classification-under-Phase-Imperfections

We implement CNN-based Automatic Modulation Classification (AMC) by applying a polar transformation to the received symbols along with a modification to the kernel dimensions of the CNN in order to improve the performance of the classification procedure under phase imperfections.

easy-few-shot-learning

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

Keras-FewShotLearning

Some State-of-the-Art few shot learning algorithms in tensorflow 2

emg-fsl

Applying few-shot learning technique (FSL) to the classification of sEMG signal.

MixMatch-pytorch

Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"

few-shot-ssl-public

Meta Learning for Semi-Supervised Few-Shot Classification

awesome-contrastive-self-supervised-learning

A comprehensive list of awesome contrastive self-supervised learning papers.

Modulation_Classification_Dataset

dataset for ICASSP2023 paper

aee-otfs

Autoencoder-Based Enhanced Orthogonal Time Frequency Space Modulation

Convolution_Transformer_Fusion-for-Automatic-Recognise-Signal-Modulation

CRAFT-SR

[ICCV2023] Implementation of "Feature Modulation Transformer: Cross-Refinement of Global Representation via High-Frequency Prior for Image Super-Resolution"

ofdm-amc

Deep learning based automatic modulation classification for sub-carriers of OFDM signals.