Course title
330339003
Media Processing 2

 TAKAHASHI Masanobu
Middle-level Diploma Policy (mDP)
Program / Major mDP Goals
IoT Course DP-4a・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Software Course DP-4b・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Media Course DP-4c・2 キャリアを見据えた高度な専門知識
画像や音響、サイバースペース等のメディア処理・デザイン技術を駆使し、社会的ニーズに適切に対応したシステムを開発できる。
Data Science Course DP-4d・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Mechatronics Course DP-4・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Architecture and Architectural Engineering Course DP-4a・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Environmental Systems and Urban Planning Course DP-4b・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Bioscience Course DP-4a・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Biomedical Engineering Course DP-4b・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Sports Engineering Course DP-4c・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Mathematical Sciences Course DP-4・3 専門分野と他分野を関連付ける素養
主軸となる分野の専門知識を他分野と関連付ける分野横断型の知識と行動力を修得し、社会で活用できる。
Purpose of class
This course covers advanced media processing techniques following Media Processing 1. Its goal is to provide practical knowledge and coding skills through related exercises.
Course description
Building on the foundations established in Media Processing 1, this course explores advanced techniques and methodologies for solving complex problems using media information such as images and speech/audio and acoustics. Through hands-on exercises, students will acquire practical knowledge and refine their programming skills. The curriculum includes more intricate tasks involving the integration of multiple media types and provides an introduction to the application of AI and machine learning.
Goals and objectives
  1. Students will be able to understand, implement, and evaluate methods for solving complex image-related challenges.
  2. Students will be able to design, implement, and present results for multimodal processing and services, including speech/audio and acoustics.
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Report Presentation Total.
1. 50% 50%
2. 40% 10% 50%
Total. 90% 10% -
Evaluation method and criteria
Grading is based on assignments (90%) and a final presentation (10%). A total score of 60% or higher is required to pass.
Language
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Guidance; Image Extraction (1): Methodologies Read the syllabus to understand the overall course content. Prepare for and review all material covered in class. 180minutes
2. Image Extraction (2): Implementation and Evaluation Writing exercise reports. 190minutes
3. Image Generation (1): Methodologies Prepare for and review all material covered in the class. 190minutes
4. Image Generation (2): Implementation and Evaluation Writing exercise reports. 190minutes
5. Image Application Systems (1): Methodologies Prepare for and review all material covered in the class. 190minutes
6. Image Application Systems (2): Methodologies Prepare for and review all material covered in the class. 190minutes
7. Image Application Systems (3): Implementation and Evaluation Writing exercise reports. 190minutes
8. Speech and Language Models (1): Service Design Prepare for and review all material covered in the class. 190minutes
9. Speech and Language Models (2): Service Implementation Writing exercise reports. 190minutes
10. Speech and Generative AI (1): Service Design Prepare for and review all material covered in the class. 190minutes
11. Speech and Generative AI (2): Service Implementation Writing exercise reports. 190minutes
12. Multimodal Processing (1): Service Design Prepare for and review all material covered in the class. 190minutes
13. Multimodal Processing (2): Service Implementation Writing exercise reports. 190minutes
14. Presentation Prepare for the presentation. 190minutes
Total. - - 2650minutes
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
Course materials will primarily be distributed as handouts. For certain sections on image processing, the textbook ’デジタル画像処理(改訂第ニ版)’ published by the CG-ARTS Society will be used.
Prerequisites
None, but please study basic introduction to programming languages (C or Python).
Office hours and How to contact professors for questions
  • Basically Friday lunch break. Other requests welcome, time permitting.
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates an ability for utilizing knowledge
  • Course that cultivates a basic problem-solving skills
Active-learning course
More than one class is interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
Applicable Leveraging Professors’ experiences in the research and development of image and speech processing and recognition systems in companies, they will teach methodologies and terminology by linking them to systems and techniques currently used in industry.
Education related SDGs:the Sustainable Development Goals
  • 4.QUALITY EDUCATION
  • 8.DECENT WORK AND ECONOMIC GROWTH
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
  • 12.RESPONSIBLE CONSUMPTION & PRODUCTION
Last modified : Tue Mar 31 04:03:08 JST 2026