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pro vyhledávání: '"Maguolo A"'
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 expedite their removal. In this paper, we generate ensembles of CNNs base
Externí odkaz:
http://arxiv.org/abs/2108.12539
Semantic segmentation has a wide array of applications ranging from medical-image analysis, scene understanding, autonomous driving and robotic navigation. This work deals with medical image segmentation and in particular with accurate polyp detectio
Externí odkaz:
http://arxiv.org/abs/2104.00850
Recently, much attention has been devoted to finding highly efficient and powerful activation functions for CNN layers. Because activation functions inject different nonlinearities between layers that affect performance, varying them is one method fo
Externí odkaz:
http://arxiv.org/abs/2103.15898
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 model in the direction of the gradient of the loss evaluated on a minibat
Externí odkaz:
http://arxiv.org/abs/2103.14689
Classification of biological images is an important task with crucial application in many fields, such as cell phenotypes recognition, detection of cell organelles and histopathological classification, and it might help in early medical diagnosis, al
Externí odkaz:
http://arxiv.org/abs/2011.11834
Publikováno v:
Journal of Imaging 2020, 6(12), 143
In this work, we present an ensemble of descriptors for the classification of transmission electron microscopy images of viruses. We propose to combine handcrafted and deep learning approaches for virus image classification. The set of handcrafted is
Externí odkaz:
http://arxiv.org/abs/2011.06123
Publikováno v:
Appl. Sci. 2021, 11(13), 5796
In this paper, ensembles of classifiers that exploit several data augmentation techniques and four signal representations for training Convolutional Neural Networks (CNNs) for audio classification are presented and tested on three freely available au
Externí odkaz:
http://arxiv.org/abs/2007.07966
Autor:
Maguolo, Gianluca, Nanni, Loris
In this paper, we compare and evaluate different testing protocols used for automatic COVID-19 diagnosis from X-Ray images in the recent literature. We show that similar results can be obtained using X-Ray images that do not contain most of the lungs
Externí odkaz:
http://arxiv.org/abs/2004.12823
Akademický článek
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Publikováno v:
Applied Computing and Informatics, Vol 19, Iss 3/4, Pp 265-283 (2023)
In this paper, we present a study about an automated system for monitoring underwater ecosystems. The system here proposed is based on the fusion of different deep learning methods. We study how to create an ensemble based of different Convolutional
Externí odkaz:
https://doaj.org/article/246ca0235e1d4c4b82642d62c49fd786
