Project inserted within the research areas of machine learning and computer vision.
[Closed]
Work description
Within the scope of the CAGED project, the collection and compilation of an annotated database of videos of gastric endoscopy exams is planned. The scholarship holder's work will take place at UTAD's facilities and it is intended that he will develop deep learning methods for detecting gastric lesions from examples to reinforce the annotation of endoscopic images and their organization and organization of the database.
Academic Qualifications
Degree in Biomedical Engineering
Minimum profile required
The fellow must have a degree in Biomedical Engineering and be a Master's student in Biomedical Engineering . Computer vision, especially in image deep learning methodologies.
Preference factors
Experience in applying deep learning methods to endoscopic images and methods for searching images from an example image.
Application Period
Since 14 Jun 2023 to 27 Jun 2023
[Closed]
Centre
Biomedical Engineering Research