PyTorch implementation of TSception V2 using DEAP dataset

Overview

TSception

This is the PyTorch implementation of TSception V2 using DEAP dataset in our paper:

Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai Guan, "TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition", under review of IEEE Transactions on Affective Computing, preprint available at arXiv

It is an end-to-end multi-scale convolutional neural network to do classification from raw EEG signals. Previous version of TSception(IJCNN'20) can be found at website

Prepare the python virtual environment

Please create an anaconda virtual environment by:

$ conda create --name TSception

Activate the virtual environment by:

$ conda activate TSception

Install the requirements by:

$ pip3 install -r requirements.txt

Run the code

Please download the DEAP dataset at website. Please place the "data_preprocessed_python" folder at the same location of the script (./code/). To run the code for arousal dimension, please type the following command in terminal:

$ python3 main-DEAP.py --data-path './data_preprocessed_python/' --label-type 'A'

To run the experiments for valance please set the --label-type 'V'. The results will be saved into "result.txt" located at the same place as the script.

Reproduce the results

We highly suggest to run the code on a Ubuntu 18.04 or above machine using anaconda with the provided requirements to reproduce the results. You can also download the saved model at website to reproduce the results in the paper. After extracting the downloaded "save.zip", please place it at the same location of the scripts, run the code by:

$ python3 main-DEAP.py --data-path './data_preprocessed_python/' --label-type 'A' --reproduce True

Acknowledgment

The author would like to thank Su Zhang, Quihao Zeng and Tushar Chouhan for checking the code

Cite

Please cite our paper if you use our code in your own work:

@misc{ding2021tsception,
      title={TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition}, 
      author={Yi Ding and Neethu Robinson and Su Zhang and Qiuhao Zeng and Cuntai Guan},
      year={2021},
      eprint={2104.02935},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

OR

@INPROCEEDINGS{9206750,
  author={Y. {Ding} and N. {Robinson} and Q. {Zeng} and D. {Chen} and A. A. {Phyo Wai} and T. -S. {Lee} and C. {Guan}},
  booktitle={2020 International Joint Conference on Neural Networks (IJCNN)}, 
  title={TSception:A Deep Learning Framework for Emotion Detection Using EEG}, 
  year={2020},
  volume={},
  number={},
  pages={1-7},
  doi={10.1109/IJCNN48605.2020.9206750}}
Owner
Yi Ding
Ph.D. candidate in Computer Science and Engineering. Research interests: deep/machine learning, brain-computer interface, artificial intelligence
Yi Ding
Jittor implementation of PCT:Point Cloud Transformer

PCT: Point Cloud Transformer This is a Jittor implementation of PCT: Point Cloud Transformer.

MenghaoGuo 547 Jan 03, 2023
TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.

TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.

Microsoft 1.3k Dec 30, 2022
Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound"

merlot_reserve Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound" MERLOT Reserve (in submission) is a mo

Rowan Zellers 92 Dec 11, 2022
Styled Handwritten Text Generation with Transformers (ICCV 21)

⚡ Handwriting Transformers [PDF] Ankan Kumar Bhunia, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan & Mubarak Shah Abstract: We

Ankan Kumar Bhunia 85 Dec 22, 2022
Predictive Maintenance LSTM

Predictive-Maintenance-LSTM - Predictive maintenance study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.

Amir M. Sadafi 1 Dec 31, 2021
This repository contains all data used for writing a research paper Multiple Object Trackers in OpenCV: A Benchmark, presented in ISIE 2021 conference in Kyoto, Japan.

OpenCV-Multiple-Object-Tracking Python is version 3.6.7 to install opencv: pip uninstall opecv-python pip uninstall opencv-contrib-python pip install

6 Dec 19, 2021
The spiritual successor to knockknock for PyTorch Lightning, get notified when your training ends

Who's there? The spiritual successor to knockknock for PyTorch Lightning, to get a notification when your training is complete or when it crashes duri

twsl 70 Oct 06, 2022
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and ap

3.4k Jan 04, 2023
Time should be taken seer-iously

TimeSeers seers - (Noun) plural form of seer - A person who foretells future events by or as if by supernatural means TimeSeers is an hierarchical Bay

279 Dec 26, 2022
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search DropNAS, a grouped operation dropout method for one-level DARTS, with better

weijunhong 4 Aug 15, 2022
Unofficial PyTorch implementation of MobileViT.

MobileViT Overview This is a PyTorch implementation of MobileViT specified in "MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Tr

Chin-Hsuan Wu 348 Dec 23, 2022
"SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image", Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, Zhangyang Wang

SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image [Paper] [Website] Pipeline Code Environment pip install -r requirements

VITA 250 Jan 05, 2023
Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds (CVPR 2022, Oral)

Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds (CVPR 2022, Oral) This is the official implementat

Yifan Zhang 259 Dec 25, 2022
A PyTorch based deep learning library for drug pair scoring.

Documentation | External Resources | Datasets | Examples ChemicalX is a deep learning library for drug-drug interaction, polypharmacy side effect and

AstraZeneca 597 Dec 30, 2022
Adaptive Graph Convolution for Point Cloud Analysis

Adaptive Graph Convolution for Point Cloud Analysis This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph

64 Dec 21, 2022
Kohei's 5th place solution for xview3 challenge

xview3-kohei-solution Usage This repository assumes that the given data set is stored in the following locations: $ ls data/input/xview3/*.csv data/in

Kohei Ozaki 2 Jan 17, 2022
Towards Debiasing NLU Models from Unknown Biases

Towards Debiasing NLU Models from Unknown Biases Abstract: NLU models often exploit biased features to achieve high dataset-specific performance witho

Ubiquitous Knowledge Processing Lab 22 Jun 14, 2022
Accompanying code for the paper "A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment".

#backdoor-HSIC (bd_HSIC) Accompanying code for the paper "A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment". To generate

Robert Hu 0 Nov 25, 2021
Non-Attentive-Tacotron - This is Pytorch Implementation of Google's Non-attentive Tacotron.

Non-attentive Tacotron - PyTorch Implementation This is Pytorch Implementation of Google's Non-attentive Tacotron, text-to-speech system. There is som

Jounghee Kim 46 Dec 19, 2022
Temporal Knowledge Graph Reasoning Triggered by Memories

MTDM Temporal Knowledge Graph Reasoning Triggered by Memories To alleviate the time dependence, we propose a memory-triggered decision-making (MTDM) n

4 Sep 25, 2022