research
∙
01/24/2022
Feature transforms for image data augmentation
A problem with Convolutional Neural Networks (CNNs) is that they require...
share
research
∙
12/24/2021
Deep ensembles in bioimage segmentation
Semantic segmentation consists in classifying each pixel of an image by ...
research
∙
10/09/2021
Gated recurrent units and temporal convolutional network for multilabel classification
Multilabel learning tackles the problem of associating a sample with mul...
research
∙
08/28/2021
High performing ensemble of convolutional neural networks for insect pest image detection
Pest infestation is a major cause of crop damage and lost revenues world...
research
∙
04/02/2021
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation
Semantic segmentation has a wide array of applications ranging from medi...
research
∙
03/26/2021
Exploiting Adam-like Optimization Algorithms to Improve the Performance of Convolutional Neural Networks
Stochastic gradient descent (SGD) is the main approach for training deep...
research
∙
11/24/2020
Comparisons among different stochastic selection of activation layers for convolutional neural networks for healthcare
Classification of biological images is an important task with crucial ap...
research
∙
08/15/2019
Deep learning for Plankton and Coral Classification
Oceans are the essential lifeblood of the Earth: they provide over 70 ox...
research
∙
08/09/2019
Learning morphological operators for skin detection
In this work we propose a novel post processing approach for skin detect...
research
∙
06/11/2019
iProStruct2D: Identifying protein structural classes by deep learning via 2D representations
In this paper we address the problem of protein classification starting ...
research
∙
07/20/2018
Ensemble of Deep Learned Features for Melanoma Classification
The aim of this work is to propose an ensemble of descriptors for Melano...
research
∙
02/07/2018
