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Sensitivity and generalized analytical sensitivity expressions for quantitative analysis using convolutional neural networks
(Elsevier Science, 2022-05)
In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; however, ...
Deep neural network approaches for Spanish sentiment analysis of short texts
(Springer Verlag, 2018)
Sentiment Analysis has been extensively researched in the last years. While important theoretical and practical results have been obtained, there is still room for improvement. In particular, when short sentences and low ...
Detection of diabetic retinopathy based on a convolutional neural network using retinal fundus images
(Springer Verlag, 2017)
Diabetic retinopathy is one of the leading causes of blindness. Its damage is associated with the deterioration of blood vessels in retina. Progression of visual impairment may be cushioned or prevented if detected early, ...
Convolutional Neural Networks with Transfer Learning for Pneumonia Detection
(Science and Information OrganizationGB, 2022)
"Pneumonia is a type of acute respiratory infection
caused by microbes, and viruses that affect the lungs. Pneumonia
is the leading cause of infant mortality in the world, accounting
for 81% of deaths in children under ...
Convolutional Neural Networks with Transfer Learning for Pneumonia Detection
(Science and Information OrganizationGB, 2022)
"Pneumonia is a type of acute respiratory infection
caused by microbes, and viruses that affect the lungs. Pneumonia
is the leading cause of infant mortality in the world, accounting
for 81% of deaths in children under ...
Efficient Breast Cancer Classification Using Histopathological Images and a Simple VGG
(Instituto de Informática - Universidade Federal do Rio Grande do Sul, 2022)
Comparison of Classical Computer Vision vs. Convolutional Neural Networks for Weed Mapping in Aerial Images
(Instituto de Informática - Universidade Federal do Rio Grande do Sul, 2020)
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 ...
Body condition estimation on cows from depth images using Convolutional Neural Networks
(Elsevier, 2018-12)
BCS (“Body Condition Score”) is a method used to estimate body fat reserves and accumulated energy balance of cows. BCS heavily influences milk production, reproduction, and health of cows. Therefore, it is important to ...
Automatic diagnostics of tuberculosis using convolutional neural networks analysis of MODS digital images
(Public Library of Science, 2019)
Tuberculosis is an infectious disease that causes ill health and death in millions of people each year worldwide. Timely diagnosis and treatment is key to full patient recovery. The Microscopic Observed Drug Susceptibility ...