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Automatic Attendance Management System based on Deep One-Shot Learning
TLDR
We proposed a solution for student attendance control using face recognition with deep one-shot learning and evaluated our approach in different conditions and image capturing devices to confirm that such a pipeline may work in a real-world setting. Expand
  • 1
Supervised Learning in the Context of Educational Data Mining to Avoid University Students Dropout
TLDR
We propose a computational approach using educational data mining and different supervised learning techniques (Decision Trees, K-nearest Neighbor, Neural Networks, Support Vector Machines, Naive Bayes and Random Forests) to evaluate the behaviour of different prediction models in order to identify the profile of at-risk university students. Expand
  • 4
Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face Recognition
TLDR
We evaluate and adapt different deep neural network architectures for the task of face super-resolution driven by face recognition performance in real-world low-resolution images. Expand