27 citations · 38 across the 5 of their papers we have counts for
10 papers
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…
Comparisons among different stochastic selection of activation layers for convolutional neural networks for healthcare
Loris Nanni, Alessandra Lumini, Stefano Ghidoni +1
Classification of biological images is an important task with crucial application in many fields, such as cell phenotypes recognition, detection of cell organelles and histopatholo…
Learning morphological operators for skin detection
Alessandra Lumini, Loris Nanni, Alice Codogno +1
In this work we propose a novel post processing approach for skin detectors based on trained morphological operators. The first step, consisting in skin segmentation is performed a…