Emotion analysis using machine learning model and deep learning model on DEAP dataset
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
| Κύριοι συγγραφείς: | , , , , |
|---|---|
| Άλλοι συγγραφείς: | |
| Μορφή: | Thesis |
| Γλώσσα: | English |
| Έκδοση: |
Brac University
2022
|
| Θέματα: | |
| Διαθέσιμο Online: | http://hdl.handle.net/10361/16788 |
| id |
10361-16788 |
|---|---|
| record_format |
dspace |
| spelling |
10361-167882022-06-01T21:03:30Z Emotion analysis using machine learning model and deep learning model on DEAP dataset Hasan, Anita Abrar, Fahim Sabur, Eshaan Tanzim Muntasir, Iftehaj Na sha, Sumaia Sadia Mostakim, Moin Parvez, Mohammad Zavid Department of Computer Science and Engineering, Brac University Deap dataset EEG Prediction Emotionomics Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 46-50). Emotion has a signi cant in uence on how you think and interact with others. It serves as a link between how you feel and the actions you take, or you could say it in uences your life decisions on occasion. Since the patterns of emotions and their re ections vary from person to person, their inquiry must be based on approaches that are e ective over a wide range of population regions. To extract features and enhance accuracy, emotion recognition using brain waves or EEG signals requires the implementation of e cient signal processing techniques. Various approaches to human-machine interaction technologies have been ongoing for a long time, and in recent years, researchers have had great success in automatically understanding emotion using brain signals. In our research, several emotional states were classi ed and tested on EEG signals collected from a well-known publicly available dataset, the DEAP Dataset, using SVM (Support Vector Machine), KNN (K-Nearest Neighbor), and an advanced Neural Network model RNN (Recurrent Neural Network) trained with LSTM (Long Short Term Memory). The main purpose of this study is to use improved ways to improve emotion recognition performance using brain signals. Emotions, on the other hand, can change with time. As a result, the changes in emotion through time are also examined in our research. Anita Hasan Fahim Abrar Eshaan Tanzim Sabur Iftehaj Muntasir Sumaia Sadia Na sha B. Computer Science 2022-06-01T06:34:50Z 2022-06-01T06:34:50Z 2021 2021-10 Thesis ID 17301221 ID 21341028 ID 16101255 ID 17301223 ID 17201030 http://hdl.handle.net/10361/16788 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 50 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Deap dataset EEG Prediction Emotionomics Machine learning |
| spellingShingle |
Deap dataset EEG Prediction Emotionomics Machine learning Hasan, Anita Abrar, Fahim Sabur, Eshaan Tanzim Muntasir, Iftehaj Na sha, Sumaia Sadia Emotion analysis using machine learning model and deep learning model on DEAP dataset |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Mostakim, Moin |
| author_facet |
Mostakim, Moin Hasan, Anita Abrar, Fahim Sabur, Eshaan Tanzim Muntasir, Iftehaj Na sha, Sumaia Sadia |
| format |
Thesis |
| author |
Hasan, Anita Abrar, Fahim Sabur, Eshaan Tanzim Muntasir, Iftehaj Na sha, Sumaia Sadia |
| author_sort |
Hasan, Anita |
| title |
Emotion analysis using machine learning model and deep learning model on DEAP dataset |
| title_short |
Emotion analysis using machine learning model and deep learning model on DEAP dataset |
| title_full |
Emotion analysis using machine learning model and deep learning model on DEAP dataset |
| title_fullStr |
Emotion analysis using machine learning model and deep learning model on DEAP dataset |
| title_full_unstemmed |
Emotion analysis using machine learning model and deep learning model on DEAP dataset |
| title_sort |
emotion analysis using machine learning model and deep learning model on deap dataset |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16788 |
| work_keys_str_mv |
AT hasananita emotionanalysisusingmachinelearningmodelanddeeplearningmodelondeapdataset AT abrarfahim emotionanalysisusingmachinelearningmodelanddeeplearningmodelondeapdataset AT sabureshaantanzim emotionanalysisusingmachinelearningmodelanddeeplearningmodelondeapdataset AT muntasiriftehaj emotionanalysisusingmachinelearningmodelanddeeplearningmodelondeapdataset AT nashasumaiasadia emotionanalysisusingmachinelearningmodelanddeeplearningmodelondeapdataset |
| _version_ |
1814308145930960896 |