Search Results - "Giacomello, Edoardo"

Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI by Kirienko, Margarita, Sollini, Martina, Ninatti, Gaia, Loiacono, Daniele, Giacomello, Edoardo, Gozzi, Noemi, Amigoni, Francesco, Mainardi, Luca, Lanzi, Pier Luca, Chiti, Arturo

“…Purpose The present scoping review aims to assess the non-inferiority of distributed learning over centrally and locally trained machine learning (ML) models…”
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Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs by Gozzi, Noemi, Giacomello, Edoardo, Sollini, Martina, Kirienko, Margarita, Ammirabile, Angela, Lanzi, Pierluca, Loiacono, Daniele, Chiti, Arturo

“…To identify the best transfer learning approach for the identification of the most frequent abnormalities on chest radiographs (CXRs), we used embeddings…”
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Searching the Latent Space of a Generative Adversarial Network to Generate DOOM Levels by Giacomello, Edoardo, Lanzi, Pier Luca, Loiacono, Daniele

“…In this work, following the same approach successfully applied to evolve Super Mario levels, we applied the CMA-ES to search the latent space of a GAN…”
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An analysis of DOOM level generation using Generative Adversarial Networks by Giacomello, Edoardo, Lanzi, Pier Luca, Loiacono, Daniele

“…Generative Adversarial Networks (GANs) learn models of data distributions that can be employed to generate synthetic data with similar characteristics. In this…”
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DOOM Level Generation Using Generative Adversarial Networks by Giacomello, Edoardo, Lanzi, Pier Luca, Loiacono, Daniele

“…We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analyzed the levels and extracted…”
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Brain MRI Tumor Segmentation with Adversarial Networks by Giacomello, Edoardo, Loiacono, Daniele, Mainardi, Luca

“…Deep Learning is a promising approach to either automate or simplify several tasks in the healthcare domain. In this work, we introduce SegAN-CAT, an…”
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Brain Magnetic Resonance Imaging Generation using Generative Adversarial Networks by Alogna, Emanuel, Giacomello, Edoardo, Loiacono, Daniele

“…Magnetic Resonance Imaging (MRI) is nowadays one of the most common medical imaging technology, due to its non-invasive nature and the many kind of supported…”
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Image Embedding and Model Ensembling for Automated Chest X-Ray Interpretation by Giacomello, Edoardo, Lanzi, Pier Luca, Loiacono, Daniele, Nassano, Luca

“…Chest X-ray (CXR) is perhaps the most frequently-performed radiological investigation globally. In this work, we present and study several machine learning…”
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Distributed Learning Approaches for Automated Chest X-Ray Diagnosis by Giacomello, Edoardo, Cataldo, Michele, Loiacono, Daniele, Lanzi, Pier Luca

“…Deep Learning has established in the latest years as a successful approach to address a great variety of tasks. Healthcare is one of the most promising field…”
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Brain MRI Tumor Segmentation with Adversarial Networks by Giacomello, Edoardo, Loiacono, Daniele, Mainardi, Luca

“…Deep Learning is a promising approach to either automate or simplify several tasks in the healthcare domain. In this work, we introduce SegAN-CAT, an approach…”
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Image Embedding and Model Ensembling for Automated Chest X-Ray Interpretation by Giacomello, Edoardo, Lanzi, Pier Luca, Loiacono, Daniele, Nassano, Luca

“…Chest X-ray (CXR) is perhaps the most frequently-performed radiological investigation globally. In this work, we present and study several machine learning…”
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DOOM Level Generation using Generative Adversarial Networks by Giacomello, Edoardo, Lanzi, Pier Luca, Loiacono, Daniele

“…We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analysed the levels and extracted…”
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