EEG signals are the modality that is widely used to recognize human emotions. However, the limited data on EEG signals remains challenging because of the small recording participants, the need for an expert to interpret EEG signals, and the expensive cost of tools to record EEG signals. This research proposed the data augmentation schemes on the EEG datasets to overcome the limited available data problem. Augmenting the data will help the generalizability of the emotion recognition model. The EEG signals on the DEAP and SEED datasets are transformed into image samples using a recurrence plot and spectrogram. Then, the artificial recurrence plot and the artificial spectrogram samples are generated using Pix2pix. This research used these artificial samples to conduct the data augmentation process. LeNet5, ResNet50, MobileNet, and DenseNet121 are used to conduct the classification. The best four data augmentation schemes are as follows: Appending 20,000 artificial recurrence plot samples to DEAP and SEED training datasets, appending 20,000 artificial spectrogram samples to the DEAP training dataset, and appending 15,000 artificial spectrogram samples to the SEED training dataset. The kappa coefficient for each classification model based on the best data augmentation schemes is computed. It is found that among the compared classifiers, LeNet5 achieved the best accuracy in both SEED (98.58%) and DEAP (86.12%) datasets when spectrogram was used. Therefore, LeNet5 trained on the spectrogram samples is a reliable and robust classification model. This finding implies that the use of spectrogram is more promising than the recurrence plot in human emotion recognition. 

An Advanced Data Augmentation Scheme on Limited EEG Signals for Human Emotion Recognition

Speech Emotion Recognition Based on Transfer Learning of Spectrogram

The COVID-19 outbreak has a significant impact on the health and well-being of the global population. The first step in the fight against COVID-19 is effective screening of infected patients. A key screening method is chest radiography. In early studies, patients showed abnormalities on chest radiographs, which were characteristic of patients with COVID-19 infection. In this paper, we use the open dataset covidx to train the neural network. covidx is composed of 13,800 chest radiographs with 13725 patients from three open case access data repositories. Novel coronavirus pneumonia was used to identify novel coronavirus pneumonia, common pneumonia and new crown pneumonia images.

The Convolutional Neural Network Used to Classify COVID-19 X-ray Images

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Wang Yan

Author Tools

Chat about Author

Papers

Speech Emotion Recognition Based on Transfer Learning of Spectrogram

The Convolutional Neural Network Used to Classify COVID-19 X-ray Images