2024 |
Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective |
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2024 |
Bacteria Taxonomic Classification using Graph Neural Networks |
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2024 |
Leveraging Deep Embeddings for Explainable Medical Image Analysis |
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2023 |
Breast Cancer Histologic Grade Identification by Graph Neural Network Embeddings |
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2023 |
Visualization and Analysis of Transformer Attention |
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2023 |
Metric Learning in Histopathological Image Classification: Opening the Black Box |
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2023 |
Deep Metric Learning for Transparent Classification of Covid-19 X-Ray Images |
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2022 |
Fuzzy Clustering of Histopathological Images Using Deep Learning Embeddings |
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2022 |
A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
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2022 |
Automatic classification of acoustically detected krill aggregations: A case study from Southern Ocean |
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2022 |
Deep Metric Learning for Histopathological Image Classification |
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2021 |
Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Issues |
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2021 |
Unsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea) |
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2021 |
Pattern Classification from Multi-beam Acoustic Data Acquired in Kongsfjorden |
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2020 |
BITS2019: The sixteenth annual meeting of the Italian society of bioinformatics |
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2020 |
CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification |
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2018 |
Bacteria classification using minimal absent words |
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2018 |
Deep learning models for bacteria taxonomic classification of metagenomic data |
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2018 |
Deep learning architectures for prediction of nucleosome positioning from sequences data |
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2018 |
Variable Ranking Feature Selection for the Identification of Nucleosome Related Sequences |
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2017 |
A Deep Learning Model for Epigenomic Studies |
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2017 |
A Deep Learning Network for Exploiting Positional Information in Nucleosome Related Sequences |
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