Goh, Yen Chang (2018) Real-time human expression recognition using deep learning on embedded system. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.
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Abstract
Technology ease human life in every aspects. Some machine save human’s effort, some machine save time and increase efficiency in work. Machine is designed to complete specific task or multiple tasks without any intelligence needed. The next level of machine is machine which has intelligent and capable to think like human being while doing jobs, moreover, learn by themselves. Recently, Machine Learning are becoming more and more popular in 21stcentury. Machine learning can explores study and algorithms construction for making prediction. Data analytic by machine learning is a trend that used by Google, Facebook, Baidu and others big company nowadays. One of data analysis in machine learning which is Human Facial Expression Recognition is one of the hot topics now. Many researchers are proposed their techniques used in emotion recognition like PCA, LBP and etc. Goal in this project, is to analyze Inception v-3, the best performing high resolution image classifier based on Convolutional Neural Network, and also implement it in Raspberry Pi to see how it performs on detecting Facial Expressions.
Item Type: | Thesis (Masters) |
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Additional Information: | Thesis (Sarjana Kejuruteraan (Komputer dan Sistem Mikroelektronik)) - Universiti Teknologi Malaysia, 2018; Supervisor : Assoc. Prof. Muhammad Mun'im Ahmad Zabidi |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 79302 |
Deposited By: | Widya Wahid |
Deposited On: | 14 Oct 2018 08:42 |
Last Modified: | 14 Oct 2018 08:42 |
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