Exercise in Affective Computing

Course Purpose
The purpose of this exercise course is for students to utilize the methods based on 'Affective Computing' upon actual research topics.
Learning Goals
Students will understand the various methods and develop problem-solving skills through task understanding, experimental design, carrying out experiments, processing and analyzing data and observations (interpretation and evaluation of the result). Python programming will be used. Students will be also able to write experimental reports and make a presentation.
Topic
Session 1Statistical analysis (1) Pairwise comparison method
Session 2Statistical analysis (2) Analysis of variance
Session 3Statistical analysis (3) Test
Session 4Machine learning (1) Extraction of texture features (Neural Style Transfer)
Session 5Machine learning (2) Lasso regression
Session 6Machine learning (3) Kansei texture estimation
Session 7Experimental design
Session 8Experiment implementation (1)
Session 9Experiment implementation (2)
Session 10Experimental data analysis
Session 11Presentation preparation
Session 12Presentation (1)
Session 13Presentation (2)
Session 14Consideration, report creation, and summary
＊＊This content is based on April 1, 2024. For the latest syllabus information and details, please check the syllabus information inquiry page provided by the university.＊＊