47 citations · 138 across the 12 of their papers we have counts for
6 papers · 1 filter
Deep ensembles in bioimage segmentation
Loris Nanni, Daniela Cuza, Alessandra Lumini +2
Semantic segmentation consists in classifying each pixel of an image by assigning it to a specific label chosen from a set of all the available ones. During the last few years, a l…
Gated recurrent units and temporal convolutional network for multilabel classification
Loris Nanni, Alessandra Lumini, Alessandro Manfe +3
Multilabel learning tackles the problem of associating a sample with multiple class labels. This work proposes a new ensemble method for managing multilabel classification: the cor…
High performing ensemble of convolutional neural networks for insect pest image detection
Loris Nanni, Alessandro Manfe, Gianluca Maguolo +2
Pest infestation is a major cause of crop damage and lost revenues worldwide. Automatic identification of invasive insects would greatly speedup the identification of pests and exp…
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation
Alessandra Lumini, Loris Nanni, Gianluca Maguolo
Semantic segmentation has a wide array of applications ranging from medical-image analysis, scene understanding, autonomous driving and robotic navigation. This work deals with med…
Exploiting Adam-like Optimization Algorithms to Improve the Performance of Convolutional Neural Networks
Loris Nanni, Gianluca Maguolo, Alessandra Lumini
Stochastic gradient descent (SGD) is the main approach for training deep networks: it moves towards the optimum of the cost function by iteratively updating the parameters of a mod…
Neural networks for Anatomical Therapeutic Chemical (ATC) classification
Loris Nanni, Alessandra Lumini, Sheryl Brahnam
Motivation: Automatic Anatomical Therapeutic Chemical (ATC) classification is a critical and highly competitive area of research in bioinformatics because of its potential for expe…