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Deep Learning Assisted Medical Insurance Data Analytics With Multimedia System
Big Data presents considerable challenges to deep learning for transforming complex, high-dimensional, and heterogeneous biomedical data into health care data. Various kinds of data are analyzed in recent biomedical research ...
Um novo espaço de similaridade projetado para o aprendizado supervisionado de métricas profundas
(Universidade Federal de Minas GeraisBrasilICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃOPrograma de Pós-Graduação em Ciência da ComputaçãoUFMG, 2021-03-05)
We propose a novel deep metric learning method. Differently from many works in this area, we defined a novel latent space obtained through an autoencoder. The new space, namely S-space, is divided into different regions ...
Deep Learning for Diabetic Retinopathy Prediction
Diabetic retinopathy is a complication of diabetes mellitus. Its early diagnosis can prevent its progression and avoid the development of other major complications such as blindness. Deep learning and transfer learning ...
Deep learning techniques for recommender systems based on collaborative filtering
(Wiley-Blackwell, 2020-11-14)
In the Big Data Era, recommender systems perform a fundamental role in data management and information filtering. In this context, Collaborative Filtering (CF) persists as one of the most prominent strategies to effectively ...
A Chaotic Maps-Based Privacy-Preserving Distributed Deep Learning for Incomplete and Non-IID Datasets
(IEEE Computer Society, 2024)
Promising Deep Semantic Nuclei Segmentation Models for Multi-Institutional Histopathology Images of Different Organs
Nuclei segmentation in whole-slide imaging (WSI) plays a crucial role in the field of computational pathology. It is a fundamental task for different applications, such as cancer cell type classification, cancer grading, ...
LexToMap: lexical-based topological mapping
(11/30/2016)
Any robot should be provided with a proper representation of its environment in order to perform navigation and other tasks. In addition to metrical approaches, topological mapping generates graph representations in which ...
A deep learning approach for sentiment analysis in Spanish Tweets
(Springer Verlag, 2018)
Sentiment Analysis at Document Level is a well-known problem in Natural Language Processing (NLP), being considered as a reference in NLP, over which new architectures and models are tested in order to compare metrics that ...