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BreastNet: Breast cancer categorization using convolutional neural networks
(2020-07-01)
Breast cancer is usually classified as either benign or malignant, where the former is not considered hazardous to health. Nonetheless, the benign tumors must be periodically monitored to control their activity and to ...
Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification
(2018-05-01)
Background and objective: Parkinson's disease (PD) is considered a degenerative disorder that affects the motor system, which may cause tremors, micrography, and the freezing of gait. Although PD is related to the lack of ...
Semi-supervised learning with convolutional neural networks for UAV images automatic recognition
(Elsevier B.V., 2019-09-01)
The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
Semi-supervised learning with connectivity-driven convolutional neural networks
(2019-12-01)
The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
Convolutional neural networks applied for Parkinson’s disease identification
(2016-01-01)
Parkinson’s Disease (PD) is a chronic and progressive illness that affects hundreds of thousands of people worldwide. Although it is quite easy to identify someone affected by PD when the illness shows itself (e.g. tremors, ...
Using convolutional neural networks in robots with limited computational resources: Detecting NAO robots while playing soccer
(Springer Verlag, 2018)
The main goal of this paper is to analyze the general problem of using Convolutional Neural Networks (CNNs) in robots with limited computational capabilities, and to propose general design guidelines for their use. In ...
An efficient convolutional neural network to detect and count blood cells
(Universidad Nacional, Costa Rica, 2022)