Search Results for author:
Found 6 papers, 3 papers with code
Spectrogram-Based Detection of Auto-Tuned Vocals in Music Recordings
In the domain of music production and audio processing, the implementation of automatic pitch correction of the singing voice, also known as Auto-Tune, has significantly transformed the landscape of vocal performance.
Fighting the scanner effect in brain MRI segmentation with a progressive level-of-detail network trained on multi-site data
We ensure robustness across sites by training the model on an unprecedented rich dataset aggregating data from open repositories: almost 27, 000 T1w volumes from around 160 acquisition sites, at 1. 5 - 3T, from a population spanning from 8 to 90 years old.
CineScale: A dataset of cinematic shot scale in movies
We provide a database containing shot scale annotations (i. e., the apparent distance of the camera from the subject of a filmed scene) for more than 792, 000 image frames.
BS-Net: learning COVID-19 pneumonia severity on a large Chest X-Ray dataset
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays images (CXR), a multi-regional score conveying the degree of lung compromise in COVID-19 patients.
CEREBRUM: a fast and fully-volumetric Convolutional Encoder-decodeR for weakly-supervised sEgmentation of BRain strUctures from out-of-the-scanner MRI
Many functional and structural neuroimaging studies call for accurate morphometric segmentation of different brain structures starting from image intensity values of MRI scans.
Deep driven fMRI decoding of visual categories
Deep neural networks have been developed drawing inspiration from the brain visual pathway, implementing an end-to-end approach: from image data to video object classes.
