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MONACO, SIMONE
Dipartimento di Automatica e Informatica
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Tandem: a Confidence-based Approach for Precise Medical Image Segmentation
In corso di stampa Monaco, Simone; Petrosino, Lorenzo; Xinaris, Christodoulos; Apiletti, Daniele
AI models for automated segmentation of engineered polycystic kidney tubules
2024 Monaco, Simone; Bussola, Nicole; Buttò, Sara; Sona, Diego; Giobergia, Flavio; Jurman, Giuseppe; Xinaris, Christodoulos; Apiletti, Daniele
Deep Probability Segmentation: Are segmentation models probability estimators?
2024 Fassio, Simone; Monaco, Simone; Apiletti, Daniele
Uncertainty-aware segmentation for rainfall prediction post processing
2024 Monaco, Simone; Monaco, Luca; Apiletti, Daniele
baρtti at GeoLingIt: Beyond Boundaries, Enhancing Geolocation Prediction and Dialect Classification on Social Media in Italy
2023 Koudounas, Alkis; Giobergia, Flavio; Benedetto, Irene; Monaco, Simone; Cagliero, Luca; Apiletti, Daniele; Baralis, ELENA MARIA
Lorentz-invariant augmentation for high-energy physics
2023 Monaco, Simone; Barresi, Sebastiano; Apiletti, Daniele
Training physics-informed neural networks: One learning to rule them all?
2023 Monaco, Simone; Apiletti, Daniele
A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery
2022 Colomba, Luca; Farasin, Alessandro; Monaco, Simone; Greco, Salvatore; Garza, Paolo; Apiletti, Daniele; Baralis, Elena; Cerquitelli, Tania
Experimental Comparison of Theory-Guided Deep Learning Algorithms
2022 Monaco, Simone; Apiletti, Daniele
Exploring waste-collection fleet data: challenges in a real-world use case from multiple data providers
2022 Monaco, Simone; Bethaz, Paolo; Apiletti, Daniele; Baldini, Fabrizio Pio; Caso, Carlo; Cerquitelli, Tania
Theory-Guided Deep Learning Algorithms: An Experimental Evaluation
2022 Monaco, Simone; Apiletti, Daniele; Malnati, Giovanni
A hybrid cloud-to-edge predictive maintenance platform
2021 Marguglio, Angelo; Veneziano, Giuseppe; Greco, Pietro; Jung, Sven; Siegburg, Robert; Schmitt, Robert H.; Monaco, Simone; Apiletti, Daniele; Nikolakis, Nikolaos; Cerquitelli, Tania; Macii, Enrico
Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction
2021 Monaco, Simone; Greco, Salvatore; Farasin, Alessandro; Colomba, Luca; Apiletti, Daniele; Garza, Paolo; Cerquitelli, Tania; Baralis, Elena
Cyst segmentation on kidney tubules by means of U-Net deep-learning models
2021 Monaco, Simone; Bussola, Nicole; Butto, Sara; Sona, Diego; Apiletti, Daniele; Jurman, Giuseppe; Viola, Elisa; Chierici, Marco; Xinaris, Christodoulos; Viola, Vincenzo
Double-Step deep learning framework to improve wildfire severity classification
2021 Monaco, Simone; Pasini, Andrea; Apiletti, Daniele; Colomba, Luca; Farasin, Alessandro; Garza, Paolo; Baralis, Elena
Improving Wildfire Severity Classification of Deep Learning U-Nets from Satellite Images
2020 Monaco, Simone; Pasini, Andrea; Apiletti, Daniele; Colomba, Luca; Garza, Paolo; Baralis, ELENA MARIA
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| Tandem: a Confidence-based Approach for Precise Medical Image Segmentation / Monaco, Simone; Petrosino, Lorenzo; Xinaris, Christodoulos; Apiletti, Daniele. - (In corso di stampa). (Intervento presentato al convegno 2024 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Workshops tenutosi a Barcelona (ESP) nel August 25, 2024 - August 29, 2024). | In corso di stampa | Simone MonacoDaniele Apiletti + | 27_tandem_a_confidence_based_appr.pdf |
| AI models for automated segmentation of engineered polycystic kidney tubules / Monaco, Simone; Bussola, Nicole; Buttò, Sara; Sona, Diego; Giobergia, Flavio; Jurman, Giuseppe; Xinaris, Christodoulos; Apiletti, Daniele. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 14:(2024). [10.1038/s41598-024-52677-1] | 1-gen-2024 | Monaco, SimoneGiobergia, FlavioApiletti, Daniele + | s41598-024-52677-1.pdf |
| Deep Probability Segmentation: Are segmentation models probability estimators? / Fassio, Simone; Monaco, Simone; Apiletti, Daniele. - (2024). (Intervento presentato al convegno The 18th IEEE International Conference on Application of Information and Communication Technologies (AICT) tenutosi a Torino (ITA) nel 25-27 September 2024) [10.1109/AICT61888.2024.10740436]. | 1-gen-2024 | Simone MonacoDaniele Apiletti + | 2409.12535v1.pdf; Deep_Probability_Segmentation_Are_Segmentation_Models_Probability_Estimators.pdf |
| Uncertainty-aware segmentation for rainfall prediction post processing / Monaco, Simone; Monaco, Luca; Apiletti, Daniele. - (2024). (Intervento presentato al convegno 2024 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Workshops tenutosi a Barcellona nel August 25, 2024 - August 29, 2024). | 1-gen-2024 | Simone MonacoLuca MonacoDaniele Apiletti | 2408.16792v1.pdf |
| baρtti at GeoLingIt: Beyond Boundaries, Enhancing Geolocation Prediction and Dialect Classification on Social Media in Italy / Koudounas, Alkis; Giobergia, Flavio; Benedetto, Irene; Monaco, Simone; Cagliero, Luca; Apiletti, Daniele; Baralis, ELENA MARIA. - ELETTRONICO. - 3473:(2023). (Intervento presentato al convegno EVALITA 2023 tenutosi a Parma (ITA) nel September 7th - 8th, 2023). | 1-gen-2023 | Koudounas AlkisGiobergia FlavioBenedetto IreneMonaco SimoneCagliero LucaApiletti DanieleBaralis Elena | paper16.pdf |
| Lorentz-invariant augmentation for high-energy physics / Monaco, Simone; Barresi, Sebastiano; Apiletti, Daniele. - ELETTRONICO. - (2023). (Intervento presentato al convegno European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases tenutosi a Turin (ITA) nel September 18-22 2023). | 1-gen-2023 | Monaco,SimoneBarresi,SebastianoApiletti,Daniele | - |
| Training physics-informed neural networks: One learning to rule them all? / Monaco, Simone; Apiletti, Daniele. - In: RESULTS IN ENGINEERING. - ISSN 2590-1230. - ELETTRONICO. - 18:(2023). [10.1016/j.rineng.2023.101023] | 1-gen-2023 | Simone MonacoDaniele Apiletti | 1-s2.0-S2590123023001500-main.pdf |
| A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery / Colomba, Luca; Farasin, Alessandro; Monaco, Simone; Greco, Salvatore; Garza, Paolo; Apiletti, Daniele; Baralis, Elena; Cerquitelli, Tania. - ELETTRONICO. - (2022), pp. 3893-3897. (Intervento presentato al convegno International Conference on Information and Knowledge Management (CIKM) 2022 tenutosi a Atlanta (Georgia, USA) nel 17/10/2022 - 21/10/2022) [10.1145/3511808.3557528]. | 1-gen-2022 | Colomba,LucaFarasin,AlessandroMonaco,SimoneGreco,SalvatoreGarza,PaoloApiletti,DanieleBaralis,ElenaCerquitelli,Tania | 3511808.3557528.pdf; BurnedAreaDatasetPaper.pdf |
| Experimental Comparison of Theory-Guided Deep Learning Algorithms / Monaco, Simone; Apiletti, Daniele. - ELETTRONICO. - 1652:(2022), pp. 256-265. (Intervento presentato al convegno European Conference on Advances in Databases and Information Systems (ADBIS 2022) tenutosi a Torino nel September 5-8 2022) [10.1007/978-3-031-15743-1_24]. | 1-gen-2022 | Monaco, SimoneApiletti, Daniele | - |
| Exploring waste-collection fleet data: challenges in a real-world use case from multiple data providers / Monaco, Simone; Bethaz, Paolo; Apiletti, Daniele; Baldini, Fabrizio Pio; Caso, Carlo; Cerquitelli, Tania. - (2022). (Intervento presentato al convegno EDBT/ICDT Workshop, 6th International workshop on Data Analytics solutions for Real-LIfe APplications tenutosi a Edinburgh nel March 29 - April 1, 2022). | 1-gen-2022 | Monaco, SimoneBethaz, PaoloApiletti, DanieleCerquitelli, Tania + | AI4Trucks_DarliAP2022.pdf |
| Theory-Guided Deep Learning Algorithms: An Experimental Evaluation / Monaco, Simone; Apiletti, Daniele; Malnati, Giovanni. - In: ELECTRONICS. - ISSN 2079-9292. - ELETTRONICO. - 11:18(2022). [10.3390/electronics11182850] | 1-gen-2022 | Simone MonacoDaniele ApilettiGiovanni Malnati | electronics-11-02850.pdf |
| A hybrid cloud-to-edge predictive maintenance platform / Marguglio, Angelo; Veneziano, Giuseppe; Greco, Pietro; Jung, Sven; Siegburg, Robert; Schmitt, Robert H.; Monaco, Simone; Apiletti, Daniele; Nikolakis, Nikolaos; Cerquitelli, Tania; Macii, Enrico (INFORMATION FUSION AND DATA SCIENCE). - In: Predictive Maintenance in Smart Factories / Marguglio A., Veneziano G., Greco P., Jung S., Siegburg R., Schmitt R. H., Monaco S., Apiletti D., Cerquitelli T., Nikolakis N., Macii E.. - ELETTRONICO. - [s.l] : Springer, 2021. - ISBN 978-981-16-2939-6. - pp. 19-37 [10.1007/978-981-16-2940-2_2] | 1-gen-2021 | Monaco, SimoneApiletti, DanieleCerquitelli, TaniaMacii, Enrico + | Serena_Book_Chapter2.pdf |
| Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction / Monaco, Simone; Greco, Salvatore; Farasin, Alessandro; Colomba, Luca; Apiletti, Daniele; Garza, Paolo; Cerquitelli, Tania; Baralis, Elena. - In: APPLIED SCIENCES. - ISSN 2076-3417. - ELETTRONICO. - 11:22(2021). [10.3390/app112211060] | 1-gen-2021 | Monaco, SimoneGreco, SalvatoreFarasin, AlessandroColomba, LucaApiletti, DanieleGarza, PaoloCerquitelli, TaniaBaralis, Elena | applsci-11-11060.pdf |
| Cyst segmentation on kidney tubules by means of U-Net deep-learning models / Monaco, Simone; Bussola, Nicole; Butto, Sara; Sona, Diego; Apiletti, Daniele; Jurman, Giuseppe; Viola, Elisa; Chierici, Marco; Xinaris, Christodoulos; Viola, Vincenzo. - ELETTRONICO. - (2021), pp. 3923-3926. (Intervento presentato al convegno IEEE International Conference on Big Data nel 15-18 Dec. 2021) [10.1109/BigData52589.2021.9671669]. | 1-gen-2021 | Monaco, SimoneApiletti, Daniele + | Cyst_segmentation_on_kidney_tubules_by_means_of_U-Net_deep-learning_models.pdf |
| Double-Step deep learning framework to improve wildfire severity classification / Monaco, Simone; Pasini, Andrea; Apiletti, Daniele; Colomba, Luca; Farasin, Alessandro; Garza, Paolo; Baralis, Elena. - ELETTRONICO. - (2021). (Intervento presentato al convegno Workshops of the 24th International Conference on Extending Database Technology/24th International Conference on Database Theory, EDBT-ICDT 2021 tenutosi a Nicosia (Cyprus) nel March 23-26, 2021). | 1-gen-2021 | Monaco, SimonePasini, AndreaApiletti, DanieleColomba, LucaFarasin, AlessandroGarza, PaoloBaralis, Elena | Rescue_DarliAP2020.pdf |
| Improving Wildfire Severity Classification of Deep Learning U-Nets from Satellite Images / Monaco, Simone; Pasini, Andrea; Apiletti, Daniele; Colomba, Luca; Garza, Paolo; Baralis, ELENA MARIA. - ELETTRONICO. - (2020), pp. 5786-5788. (Intervento presentato al convegno 2020 IEEE International Conference on Big Data tenutosi a Atlanta (US) nel December 10-13, 2020) [10.1109/BigData50022.2020.9377867]. | 1-gen-2020 | Simone MonacoAndrea PasiniDaniele ApilettiLuca ColombaPaolo GarzaElena Baralis | IEEE_Conference_BigData_2020.pdf; 09247550.pdf |