Search Results for author:
Found 6 papers, 3 papers with code
An Interpretable Adaptive Multiscale Attention Deep Neural Network for Tabular Data
Deep learning (DL) has been demonstrated to be a valuable tool for analyzing signals such as sounds and images, thanks to its capabilities of automatically extracting relevant patterns as well as its end-to-end training properties.
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breath
AUCO ResNet has proved to provide state of art results on many datasets.
Ranked #1 on
COVID-19 Diagnosis
on Covid-19 Cough Cambridge
Online handwriting, signature and touch dynamics: tasks and potential applications in the field of security and health
Background: An advantageous property of behavioural signals , e. g. handwriting, in contrast to morphological ones, such as iris, fingerprint, hand geometry, etc., is the possibility to ask a user for a very rich amount of different tasks.
ICDAR 2021 Competition on Components Segmentation Task of Document Photos
This paper describes the short-term competition on the Components Segmentation Task of Document Photos that was prepared in the context of the 16th International Conference on Document Analysis and Recognition (ICDAR 2021).
FCN+RL: A Fully Convolutional Network followed by Refinement Layers to Offline Handwritten Signature Segmentation
Although secular, handwritten signature is one of the most reliable biometric methods used by most countries.
LICIC: Less Important Components for Imbalanced Multiclass Classification
Multiclass classification in cancer diagnostics, using DNA or Gene Expression Signatures, but also classification of bacteria species fingerprints in MALDI-TOF mass spectrometry data, is challenging because of imbalanced data and the high number of dimensions with respect to the number of instances.
