Ciencias da Computación e Tecnoloxías da Información
Coordinador
Rouco Maseda, Jose
E-mail
jose.rouco@udc.es
Lecturers
Rouco Maseda, Jose
E-mail
jose.rouco@udc.es
Web
General description
The objective of this subject is to know and apply advanced neural models, to know the techniques of the state of the art of deep learning, with end-to-end training approaches, and minimizing the use of tagged data, to solve computer vision applications using the methodologies covered in the subject.
Contingency plan
1. Modifications to the contents
No change
2. Methodologies
All activities are maintained. The teaching will be online and the lessons will take place synchronously in the official schedule of classes. It may be that, for reasons of inconvenience, some of the classes will be held asynchronously, which will be communicated to the students in advance.
3. Mechanisms for personalized attention to students
The tutorials will be telematic and will require an appointment.
4. Modifications in the evaluation
No change in the evaluation. Evaluation activities that cannot be carried out in person will be carried out telematically through the institutional tools in Office 365 and Moodle. In this case, a series of validation measures will be required, which will require the students to have a device with a microphone and a camera, while appropriate validation software is not available. An interview may be arranged with each student to comment on or explain part or all of the tests carried out. In these scenarios, some of the activities under each heading may be modified, adapting them to the situation, but not their overall contribution to the final grade (the weighting percentage)
5. Modifications to the bibliography or webgraphy
No change
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.
Subjects
