Archivio Istituzionale della RicercaAPILETTI, DANIELE
APILETTI, DANIELE
Dipartimento di Automatica e Informatica
017160
Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment
In corso di stampa REGE CAMBRIN, Daniele; SCAFFIDI MILITONE, Gabriele; Colomba, Luca; Malnati, Giovanni; Apiletti, Daniele; Garza, Paolo
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
DriftLens: A Concept Drift Detection Tool
2024 Greco, Salvatore; Vacchetti, Bartolomeo; Apiletti, Daniele; Cerquitelli, Tania
Explaining deep convolutional models by measuring the influence of interpretable features in image classification
2024 Ventura, Francesco; Greco, Salvatore; Apiletti, Daniele; Cerquitelli, Tania
Hermes, a low-latency transactional storage for binary data streams from remote devices
2024 Scaffidi Militone, Gabriele; Apiletti, Daniele; Malnati, Giovanni
Uncertainty-aware segmentation for rainfall prediction post processing
2024 Monaco, Simone; Monaco, Luca; Apiletti, Daniele
A Model-based Curriculum Learning Strategy for Training SegFormer
2023 Rege Cambrin, Daniele; Apiletti, Daniele; Garza, Paolo
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
Combining fault-tolerant persistence and low-latency streaming access to binary data for AI models
2023 Militone, Gabriele Scaffidi; Apiletti, Daniele; Malnati, Giovanni
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
Trusting deep learning natural-language models via local and global explanations
2022 Ventura, Francesco; Greco, Salvatore; Apiletti, Daniele; Cerquitelli, Tania
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
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment / REGE CAMBRIN, Daniele; SCAFFIDI MILITONE, Gabriele; Colomba, Luca; Malnati, Giovanni; Apiletti, Daniele; Garza, Paolo. - ELETTRONICO. - (In corso di stampa). (Intervento presentato al convegno CV2: Computer Vision for Videogames Workshop at ECCV2024 tenutosi a Milano (Italy) nel 29/09/2024). | In corso di stampa | Daniele Rege CambrinGabriele Scaffidi MilitoneLuca ColombaGiovanni MalnatiDaniele ApilettiPaolo Garza | ECCV2024_CV2_arxiv.pdf |
| 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 |
| DriftLens: A Concept Drift Detection Tool / Greco, Salvatore; Vacchetti, Bartolomeo; Apiletti, Daniele; Cerquitelli, Tania. - ELETTRONICO. - 27:(2024), pp. 806-809. (Intervento presentato al convegno Proceedings 27th International Conference on Extending Database Technology ( EDBT 2024 ) tenutosi a Paestum (IT) nel 25th March - 28th March, 2024). | 1-gen-2024 | Greco, SalvatoreVacchetti, BartolomeoApiletti, DanieleCerquitelli, Tania | DriftLens - A Concept Drift Detection Tool.pdf |
| Explaining deep convolutional models by measuring the influence of interpretable features in image classification / Ventura, Francesco; Greco, Salvatore; Apiletti, Daniele; Cerquitelli, Tania. - In: DATA MINING AND KNOWLEDGE DISCOVERY. - ISSN 1573-756X. - 38:(2024), pp. 3169-3226. [10.1007/s10618-023-00915-x] | 1-gen-2024 | Ventura, FrancescoGreco, SalvatoreApiletti, DanieleCerquitelli, Tania | s10618-023-00915-x.pdf |
| Hermes, a low-latency transactional storage for binary data streams from remote devices / Scaffidi Militone, Gabriele; Apiletti, Daniele; Malnati, Giovanni. - In: DATA & KNOWLEDGE ENGINEERING. - ISSN 0169-023X. - 153:(2024). [10.1016/j.datak.2024.102315] | 1-gen-2024 | Scaffidi Militone, GabrieleApiletti, DanieleMalnati, Giovanni | 02_DKE_Hermes--a-low-latency-transactional-storage-for-binar_2024_Data---Knowledge-.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 |
| A Model-based Curriculum Learning Strategy for Training SegFormer / Rege Cambrin, Daniele; Apiletti, Daniele; Garza, Paolo. - (2023), pp. 1-6. (Intervento presentato al convegno IEEE 17th International Conference Application of Information and Communication Technologies tenutosi a Baku (AZ) nel 18-20 October 2023) [10.1109/AICT59525.2023.10313143]. | 1-gen-2023 | Rege Cambrin, DanieleApiletti, DanieleGarza, Paolo | aict.pdf; A_Model-based_Curriculum_Learning_Strategy_for_Training_SegFormer.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 |
| Combining fault-tolerant persistence and low-latency streaming access to binary data for AI models / Militone, Gabriele Scaffidi; Apiletti, Daniele; Malnati, Giovanni. - ELETTRONICO. - (2023), pp. 3149-3153. (Intervento presentato al convegno 2023 IEEE International Conference on Big Data (BigData) tenutosi a Sorrento (IT) nel 15/12/2023 - 18/12/2023) [10.1109/bigdata59044.2023.10386896]. | 1-gen-2023 | Militone, Gabriele ScaffidiApiletti, DanieleMalnati, Giovanni | Combining fault-tolerant persistence and low-latency streaming access to binary data for AI models.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 |
| Trusting deep learning natural-language models via local and global explanations / Ventura, Francesco; Greco, Salvatore; Apiletti, Daniele; Cerquitelli, Tania. - In: KNOWLEDGE AND INFORMATION SYSTEMS. - ISSN 0219-1377. - 64:(2022), pp. 1863-1907. [10.1007/s10115-022-01690-9] | 1-gen-2022 | Ventura,FrancescoGreco,SalvatoreApiletti,DanieleCerquitelli,Tania | Trusting deep learning natural-language models via local and global explanations.pdf; s10115-022-01690-9.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 |