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End-To-End Multi-Task Learning for Simultaneous Optic Disc and Cup Segmentation and Glaucoma Classification in Eye Fundus Images
(Elsevier, 2022)
[Abstract] The automated analysis of eye fundus images is crucial towards facilitating the screening and early diagnosis of glaucoma. Nowadays, there are two common alternatives for the diagnosis of this disease using deep ...
Unsupervised contrastive unpaired image generation approach for improving tuberculosis screening using chest X-ray images
(Elsevier, 2022-12)
[Abstract]: Tuberculosis is an infectious disease that mainly affects the lung tissues. Therefore, chest X-ray imaging can be very useful to diagnose and to understand the evolution of the pathology. This image modality ...
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
(Springer Nature, 2019-06-26)
[Abstract]
Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ...
Estudo da utilização de deepfakes no ciberespaço, impacto e suas consequências no ambiente social
(Associacao Portuguesa de Sistemas de Informaçao, 2022-11)
[Resumo] Vivemos numa era inundados por informações vindas de ambos os hemisférios, e em que a economia
da atenção nos torna distantes da verdade. O presente estudo tem como âmago estudar a criação,
utilização, bem como ...
An integrated inversion framework for heterogeneous aquifer structure identification with single-sample generative adversarial network
(Elsevier, 2022)
[Abstract:] Generating reasonable heterogeneous aquifer structures is essential for understanding the physicochemical processes controlling groundwater flow and solute transport better. The inversion process of aquifer ...
On the Reliability of Machine Learning Models for Survival Analysis When Cure Is a Possibility
(MDPI, 2023-10-02)
[Abstract]: In classical survival analysis, it is assumed that all the individuals will experience the event of interest. However, if there is a proportion of subjects who will never experience the event, then a standard ...
LyS at TASS 2015: Deep Learning Experiments for Sentiment Analysis on Spanish Tweets
(CEUR-WS Workshop Proceedings, 2015)
[Abstract]: This paper describes the participation of the LyS group at tass 2015. In
this year’s edition, we used a long short-term memory neural network to address the
two proposed challenges: (1) sentiment analysis at ...
Using Machine Learning to Collect and Facilitate Remote Access to Biomedical Databases: Development of the Biomedical Database Inventory
(J M I R Publications, Inc., 2021-02-25)
[Abstract]
Background:
Currently, existing biomedical literature repositories do not commonly provide users with specific means to locate and remotely access biomedical databases.
Objective:
To address this issue, ...
Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images From Portable Devices
(Institute of Electrical and Electronics Engineers, 2020-10-26)
[Abstract]
The recent human coronavirus disease (COVID-19) is a respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the effects of COVID-19 in pulmonary tissues, chest ...
Using the Power Delay Profile to Accelerate the Training of Neural Network-Based Classifiers for the Identification of LOS and NLOS UWB Propagation Conditions
(Institute of Electrical and Electronics Engineers, 2020)
[Abstract]: Ultra-wideband (UWB) technology enables centimeter-level localization systems based on the accurate estimation of the actual distance between transmitter and receiver, by means of the precise estimation of the ...