"Brahnam, Sheryl" - Selaus tekijän mukaan TUNICRIS-julkaisut
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Comparison of Different Convolutional Neural Network Activation Functions and Methods for Building Ensembles for Small to Midsize Medical Data Sets
Nanni, Loris; Brahnam, Sheryl; Paci, Michelangelo; Ghidoni, Stefano (16.08.2022)
article<p>CNNs and other deep learners are now state-of-the-art in medical imaging research. However, the small sample size of many medical data sets dampens performance and results in overfitting. In some medical areas, ... -
Comparison of Different Image Data Augmentation Approaches
Nanni, Loris; Paci, Michelangelo; Brahnam, Sheryl; Lumini, Alessandra (27.11.2021)
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An ensemble of convolutional neural networks for audio classification
Nanni, Loris; Maguolo, Gianluca; Brahnam, Sheryl; Paci, Michelangelo (06 / 2021)
articleResearch in sound classification and recognition is rapidly advancing in the field of pattern recognition. One important area in this field is environmental sound recognition, whether it concerns the identification of ... -
Feature transforms for image data augmentation
Nanni, Loris; Paci, Michelangelo; Brahnam, Sheryl; Lumini, Alessandra (2022)
articleA problem with convolutional neural networks (CNNs) is that they require large datasets to obtain adequate robustness; on small datasets, they are prone to overfitting. Many methods have been proposed to overcome this ... -
Varied Image Data Augmentation Methods for Building Ensemble
Bravin, Riccardo; Nanni, Loris; Loreggia, Andrea; Brahnam, Sheryl; Paci, Michelangelo (2023)
articleConvolutional Neural Networks (CNNs) are used in many domains but the requirement of large datasets for robust training sessions and no overfitting makes them hard to apply in medical fields and similar fields. However, ...