activity
20182021
most citedLearning morphological operators for skin detection

27 citations · 38 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2021

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…

cs.CV20214 cited

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…

cs.CV20202 cited

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…

cs.CV201927 cited

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…

cs.CV2019

Deep learning for Plankton and Coral Classification

Alessandra Lumini, Loris Nanni, Gianluca Maguolo

Oceans are the essential lifeblood of the Earth: they provide over 70% of the oxygen and over 97% of the water. Plankton and corals are two of the most fundamental components of oc…

cs.CV2019

iProStruct2D: Identifying protein structural classes by deep learning via 2D representations

Loris Nanni, Alessandra Lumini, Federica Pasquali +1

In this paper we address the problem of protein classification starting from a multi-view 2D representation of proteins. From each 3D protein structure, a large set of 2D projectio…