5 citations · 11 across the 5 of their papers we have counts for
7 papers · 1 filter
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…
Comparison of different convolutional neural network activation functions and methods for building ensembles
Loris Nanni, Gianluca Maguolo, Sheryl Brahnam +1
Recently, much attention has been devoted to finding highly efficient and powerful activation functions for CNN layers. Because activation functions inject different nonlinearities…
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…
Insect pest image detection and recognition based on bio-inspired methods
Loris Nanni, Gianluca Maguolo, Fabio Pancino
Insect pests recognition is necessary for crop protection in many areas of the world. In this paper we propose an automatic classifier based on the fusion between saliency methods…
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…