# DGMM

**Repository Path**: HavenKey/DGMM

## Basic Information

- **Project Name**: DGMM
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-11-26
- **Last Updated**: 2021-11-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Code for paper “Reconstructing Perceived Images from Human Brain Activities with Bayesian Deep Multi-view Learning”
> - Authors: Changde Du, Changying Du, Lijie Huang, Huiguang He

This repository contains the implementation of the Deep Generative Multi-view Model (DGMM) described in
[Sharing deep generative representation for perceived image reconstruction from human brain activity](https://ieeexplore.ieee.org/document/7965968) and [Reconstructing Perceived Images from Human Brain Activities with Bayesian Deep Multi-view Learning](https://ieeexplore.ieee.org/document/8574054). 

![Graphical models](Pro.png)
![Illustration of the proposed DGMM framework](framework.png)
![Resluts](69results.png)


## Dependencies

- Keras
- numpy
- scipy
- matlab

## Usage

- run the file DGMM_Keras.py directly. 

## Cite

Please cite our paper if you use this code in your own work:
```
@article{du2018reconstructing,
  title={Reconstructing Perceived Images from Human Brain Activities with Bayesian Deep Multi-view Learning},
  author={Du, Changde and Du, Changying and Huang, Lijie and He, Huiguang},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2018}
}
```

```
@inproceedings{du2017sharing,
  title={Sharing deep generative representation for perceived image reconstruction from human brain activity},
  author={Du, Changde and Du, Changying and He, Huiguang},
  booktitle={IJCNN},
  year={2017}
}
```