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
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
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
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
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
DSLE: A Smart Platform for Designing Data Science Competitions
2020 Attanasio, Giuseppe; Giobergia, Flavio; Pasini, Andrea; Ventura, Francesco; Baralis, ELENA MARIA; Cagliero, Luca; Garza, Paolo; Apiletti, Daniele; Cerquitelli, Tania; Chiusano, SILVIA ANNA
Evaluating espresso coffee quality by means of time-series feature engineering
2020 Apiletti, D.; Pastor, E.; Callà, R.; Baralis, E.
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
A new unsupervised predictive-model self-assessment approach that SCALEs
2019 Ventura, Francesco; Proto, Stefano; Apiletti, Daniele; Cerquitelli, Tania; Panicucci, Simone; Baralis, Elena; Macii, Enrico; Macii, Alberto
PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes
2019 Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Cerquitelli, Tania; Baralis, ELENA MARIA; Macii, Enrico; Macii, Alberto
Towards a real-time unsupervised estimation of predictive model degradation
2019 Cerquitelli, Tania; Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Baralis, ELENA MARIA
| 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 |
| 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 |
| 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 | - |
| 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 |
| 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 |
| DSLE: A Smart Platform for Designing Data Science Competitions / Attanasio, Giuseppe; Giobergia, Flavio; Pasini, Andrea; Ventura, Francesco; Baralis, ELENA MARIA; Cagliero, Luca; Garza, Paolo; Apiletti, Daniele; Cerquitelli, Tania; Chiusano, SILVIA ANNA. - ELETTRONICO. - (2020), pp. 133-142. (Intervento presentato al convegno 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC) tenutosi a Madrid (Spain) nel July 13-17) [10.1109/COMPSAC48688.2020.00026]. | 1-gen-2020 | Giuseppe AttanasioFlavio GiobergiaAndrea PasiniFrancesco VenturaElena BaralisLuca CaglieroPaolo GarzaDaniele ApilettiTania CerquitelliSilvia Chiusano | 730300a133.pdf; DSL_IEEECompsac2020_accepted_version.pdf |
| Evaluating espresso coffee quality by means of time-series feature engineering / Apiletti, D.; Pastor, E.; Callà, R.; Baralis, E.. - ELETTRONICO. - 2578:(2020). (Intervento presentato al convegno Workshops of the 23rd International Conference on Extending Database Technology/23rd International Conference on Database Theory, EDBT-ICDT-WS 2020 tenutosi a Copenhagen (DNK) nel March 30, 2020). | 1-gen-2020 | Apiletti D.Pastor E.Baralis E. + | DARLIAP5.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 |
| A new unsupervised predictive-model self-assessment approach that SCALEs / Ventura, Francesco; Proto, Stefano; Apiletti, Daniele; Cerquitelli, Tania; Panicucci, Simone; Baralis, Elena; Macii, Enrico; Macii, Alberto. - ELETTRONICO. - 2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019:(2019), pp. 144-148. (Intervento presentato al convegno 2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019 tenutosi a Milan, Italy nel July 8-13, 2019) [10.1109/BigDataCongress.2019.00033]. | 1-gen-2019 | Ventura FrancescoProto StefanoApiletti DanieleCerquitelli TaniaBaralis ElenaMacii EnricoMacii Alberto + | - |
| PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes / Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Cerquitelli, Tania; Baralis, ELENA MARIA; Macii, Enrico; Macii, Alberto. - ELETTRONICO. - 2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019:(2019), pp. 139-143. (Intervento presentato al convegno 2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019 tenutosi a Milan, Italy nel July 8-13, 2019) [10.1109/BigDataCongress.2019.00032]. | 1-gen-2019 | Stefano ProtoFrancesco VenturaDaniele ApilettiTania CerquitelliElena BaralisEnrico MaciiAlberto Macii | - |
| Towards a real-time unsupervised estimation of predictive model degradation / Cerquitelli, Tania; Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Baralis, ELENA MARIA. - ELETTRONICO. - (2019). (Intervento presentato al convegno BIRTE '19 International Workshop on Real-Time Business Intelligence and Analytics tenutosi a Los Angeles, CA, USA nel August 26, 2019) [10.1145/3350489.3350494]. | 1-gen-2019 | Tania CerquitelliStefano ProtoFrancesco VenturaDaniele ApilettiElena Baralis | - |