| 開講学期／Course Start | 2019年度／Academic Year 後期／Second |
|---|---|
| 開講曜限／Class period | 水/Wed 1,水/Wed 2,水/Wed 3,水/Wed 4 |
| 授業区分／Regular or Intensive | 週間授業 |
| 対象学科／Department | 情報電子工学系専攻知能情報学コース |
| 対象学年／Year | 1年,2年 |
| 授業科目区分／Category | 博士前期課程 大学院自専攻科目 |
| 必修・選択／Mandatory or Elective | 選択 |
| 授業方法／Lecture or Seminar | 講義科目 |
| 授業科目名／Course Title | 認知情報処理特論Ｂ |
| 単位数／Number of Credits | 2.0 |
| 担当教員名／Lecturer | 佐賀聡人 |
| 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 | 2019/01/23 |
|---|---|
| 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] |
| 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. |
| 履修上の注意 ／Notices |
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| 教員メッセージ ／Message from Lecturer |
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| 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 |
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| 該当するデータはありません | ||||
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Active learning 1-1 ／主体的学修（反転授業，小テスト，振り返り 等） |
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Active learning 1-2 ／上記項目に係るALの度合い |
該当なし |
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Active learning 2-1 ／対話的学修（グループ学習，協働，調査体験 等） |
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Active learning 2-2 ／上記項目に係るALの度合い |
該当なし |
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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） |
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Active learning 3-2 ／上記項目に係るALの度合い |
該当なし |