Educational guide School of Engineering |
english |
Computer Security Engineering and Artificial Intelligence (2016) |
Subjects |
ARTIFICIAL VISION AND PATTERN RECOGNITION |
Learning outcomes |
IDENTIFYING DATA | 2019_20 |
Subject | ARTIFICIAL VISION AND PATTERN RECOGNITION | Code | 17685105 | |||||
Study programme |
|
Cycle | 2nd | |||||
Descriptors | Credits | Type | Year | Period | ||||
4.5 | Compulsory | First | 1Q |
Competences | Learning outcomes | Contents |
Planning | Methodologies | Personalized attention |
Assessment | Sources of information | Recommendations |
Type A | Code | Learning outcomes |
A1 |
Analyse the problems and their causes from a global focus in the medium and long term. | |
A8 |
Develop advanced artificial vision techniques in cameras and other embedded and ubiquitous systems. | |
A9 |
Know how to implement advanced computer vision techniques. | |
A10 |
Use graphic computation techniques. | |
A11 |
Use artificial systems that interact with humans by means of artificial vision. | |
A12 |
Analyse multimedia content using pattern recognition and artificial vision techniques. | |
G1 |
Integrate theoretical knowledge into the realities to which it may apply. | |
G2 |
Apply the techniques learned in a specific context. | |
Type B | Code | Learning outcomes |
CT2 |
Manage information and knowledge by making efficient use of the information technologies. | |
CT3 |
Recognise the situation as a problem in a multidisciplinary, research or professional environment, and take an active part in finding a solution. | |
CT4 |
Participate in the group in a good working environment and help to solve problems. | |
CT5 |
Produce a persuasive, consistent and precise discourse that can explain complex ideas and effectively interact with the audience. | |
CT7 |
Apply ethical and socially responsible principles as a citizen and a professional. | |
Type C | Code | Learning outcomes |