0000000000765989
AUTHOR
Alberto Solano
Deep Learning Architectures for Diagnosis of Diabetic Retinopathy
For many years, convolutional neural networks dominated the field of computer vision, not least in the medical field, where problems such as image segmentation were addressed by such networks as the U-Net. The arrival of self-attention-based networks to the field of computer vision through ViTs seems to have changed the trend of using standard convolutions. Throughout this work, we apply different architectures such as U-Net, ViTs and ConvMixer, to compare their performance on a medical semantic segmentation problem. All the models have been trained from scratch on the DRIVE dataset and evaluated on their private counterparts to assess which of the models performed better in the segmentatio…
Analysis of the Pre and Post-COVID-19 Lockdown Use of Smartphone Apps in Spain
The global pandemic of COVID-19 has changed our daily habits and has undoubtedly affected our smartphone usage time. This paper attempts to characterize the changes in the time of use of smartphones and their applications between the pre-lockdown and post-lockdown periods in Spain, during the first COVID-19 confinement in 2020. This study analyzes data from 1940 participants, which was obtained both from a survey and from a tracking application installed on their smartphones. We propose manifold learning techniques such as clustering, to assess, both in a quantitative and in a qualitative way, the behavioral and social effects and implications of confinement in the Spanish population. We al…