This page gathers all Deep Learning applications developed at IFCA by the Advanced Computing and e-Science Group.
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We trained an deep learning model to try to predict COVID incidence using cur [...]
This usecase intends to link large-scale atmospheric variables with the local [...]
We use use a deep learning classifier to accurately predict water depth (bath [...]
We use use a deep learning classifier to accurately predict water quality (al [...]
We train an image classifier to classify events of the DAMIC-M (DArk Matter [...]
We use use a deep learning classifier to accurately detect and monitor forest [...]
The final goal of the project is to prepare a new generation of e-infrastruct [...]
The work deals with a proactive network monitoring for security and protectio [...]
We use Deep Learning to upscale the multispectral images of several satellite [...]
We trained an audio classifier to identify bird species from bird sounds.
The aim improve classification speed and accuracy of chest X-ray images. In t [...]
We trained an image classifier to identify conus marine snails at species lev [...]
We trained an image classifier to identify phytoplankton in collaboration wit [...]
We trained an image classifier to identify seed images in collaboration with [...]
We used an autoencoder to learn in an unsupervised manner the distribution of [...]
We trained an image classifier to identify zooplankton in collaboration with [...]
We trained an image classifier to identify plants species. In a first iterati [...]
The application of deep learning techniques using convolutional neural networ [...]