165 citations · 536 across the 24 of their papers we have counts for
8 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…
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…
Deep Features for training Support Vector Machine
Loris Nanni, Stefano Ghidoni, Sheryl Brahnam
Features play a crucial role in computer vision. Initially designed to detect salient elements by means of handcrafted algorithms, features are now often learned by different layer…