165 citations · 307 across the 10 of their papers we have counts for
13 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…
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…
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…
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…
An Ensemble of Convolutional Neural Networks for Audio Classification
Loris Nanni, Gianluca Maguolo, Sheryl Brahnam +1
In this paper, ensembles of classifiers that exploit several data augmentation techniques and four signal representations for training Convolutional Neural Networks (CNNs) for audi…