- Collaborate on a survey on the state of the art on equivariance in deep learning; - Implement deep learning models equivariant to rotation and scale for feature extraction; - Compare the accuracy of different implemented solutions; - Write the final activity report.
The main objectives of this grant are: a) to expand the state of the art in rotation and scale equivariant deep learning models; b) to develop and evaluate solutions for common tasks in fingerprint image analysis using these models; c) to develop critical thinking.
Minimum profile required
Minimum graduation and masters grades of 14 values.Previous experience in biometrics and deep learning;
Knowledge in programming (ex: python); Knowledge in deep learning frameworks
Since 27 Jul 2022 to 10 Aug 2022
Cluster / Centre
Networked Intelligent Systems / Telecommunications and Multimedia