授業情報/Course information

開講学期/Course Start
開講曜限/Class period
授業区分/Regular or Intensive
対象学科/Department
対象学年/Year
授業科目区分/Category
必修・選択/Mandatory or Elective
授業方法/Lecture or Seminar
授業科目名/Course Title
単位数/Number of Credits
担当教員名/Lecturer
時間割コード/Registration Code MQ317
連絡先/Contact 佐賀聡人(教員室:V501 連絡先E-mail: saga@csse.muroran-it.ac.jp)
オフィスアワー/Office hours 佐賀聡人(金曜日 14:00-15:00)
実務経験/Work experience
更新日/Date of renewal 2020/06/29
授業のねらい
/Learning Objectives
This subject is designed for students to carefully consider cognitive mechanisms of  humans by taking up a rough-symmetry detection problem in  natural images as an example.
到達度目標
/Outcomes Measured By:
1. Get ability to run several algorithms about image processing.
2. Get ability to perform some experiments on cognitive mechanisms.
3. Get ability to make some discussions on cognitive mechanisms.
授業計画
/Course Schedule
Total hours: 22.5

No.  1 Image feature point detection (1) [lecture]
No.  2 Image feature point detection (2) [lecture]
No.  3 Implementation of feature point detection (1) [exercise]
No.  4 Implementation of feature point detection (2) [exercise]
No.  5 Experiment on feature point detection (1) [exercise]
No.  6 Experiment on feature point detection (2) [exercise]
No.  7 Hough transform and line detection [lecture]
No.  8 Fuzzy model for feature points [lecture]
No.  9 Fuzzy-symmetry detection algorithm (1) [lecture]
No. 10 Fuzzy-symmetry detection algorithm (2) [lecture]
No. 11 Installation of fuzzy-symmetry detection program [exercise]
No. 12 Experiment on fuzzy-symmetry detection (1) [exercise]
No. 13 Experiment on fuzzy-symmetry detection (2) [exercise]
No. 14 Experiment on fuzzy-symmetry detection (3) [exercise]
No. 15 Presentations and discussions [lecture]

新型コロナウイルス感染症の流行状況に伴い、学生への十分な周知のもと、授業計画・授業実施方法は変更する可能性があります。
Due to the epidemic situation of COVID19, the plan and implementation method may be changed.
In that case, I will explain to you properly.
教科書・参考書に関する備考 Materials will be distributed in the class as needed.
成績評価方法
/Grading Guidelines
To pass the course, 60 marks or more are required out of a maximum 100.
The marks of each student are given based on the submitted reports.

新型コロナウイルス感染症の流行状況に伴い、学生への十分な周知のもと、成績評価方法は変更する可能性があります。
Due to the epidemic situation of COVID19, the evaluation method may be changed.
In that case, I will explain to you properly.
履修上の注意
/Notices
教員メッセージ
/Message from Lecturer
学習・教育目標との対応
/Learning and Educational Policy
This course is relate to all the educational policies of Computer Systemics Course and Intelligent Informatics Cource in Division of Information and Electronic Engineering.
関連科目
/Related course
Advanced Cognitive Information Processing A
備考
/Notes
Used language: Japanese
No. 回(日時)
/Time (date and time)
主題と位置付け(担当)
/Subjects and instructor's position
学習方法と内容
/Methods and contents
備考
/Notes
該当するデータはありません
Active learning 1-1
/主体的学修(反転授業,小テスト,振り返り 等)
Active learning 1-2
/上記項目に係るALの度合い
該当なし
Active learning 2-1
/対話的学修(グループ学習,協働,調査体験 等)
Active learning 2-2
/上記項目に係るALの度合い
該当なし
Active learning 3-1
/深い学修(複数科目の知識の総合化や問題解決型学修 等)
Active learning 3-2
/上記項目に係るALの度合い
該当なし