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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Computer Vision I |
| Methodologies |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Computer Vision I | Code | 614544017 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 1st four-month period |
First | Obligatory | 3 | ||||||||||
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| Methodologies | Description |
| Guest lecture / keynote speech | The teacher presents a topic to the students with the aim of providing a set of information with a specific scope. This teaching methodology will be applied to the training activity "Theory classes". |
| Laboratory practice | The teaching staff of the subject poses to the students a problem or problems of a practical nature whose resolution requires the understanding and application of the theoretical-practical contents included in the contents of the subject. Students can work on the solution to the problems raised individually or in groups. This teaching methodology will be applied to the training activity "Practical laboratory classes" and may be applied to the training activity of "Problem-based learning sessions, seminars, case studies and projects". |
| Case study | Students are presented with a work scenario, real or fictitious, that presents a certain problem. Students must apply the theoretical-practical knowledge of the subject to find a solution to the question or questions raised. As a general rule, the case study will be carried out in groups. The different working groups will present and share their solutions. |
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