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ORCIDFederico A. Galatolo
Person information
- affiliation (PhD 2022): University of Pisa, Department of Information Engineering, Pisa, Italy
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2020 – today
- 2024
[j5]Marco Parola
, Federico A. Galatolo, Gaetano La Mantia, Mario G. C. A. Cimino, Giuseppina Campisi, Olga Di Fede:
Towards explainable oral cancer recognition: Screening on imperfect images via Informed Deep Learning and Case-Based Reasoning. Comput. Medical Imaging Graph. 117: 102433 (2024)- [j4]Federico A. Galatolo, Mario G. C. A. Cimino:
Optimizing sparse topologies via competitive joint unstructured neural networks. Prog. Artif. Intell. 13(4): 335-349 (2024) - [c21]Alessio Cascione, Mattia Setzu, Federico A. Galatolo, Mario G. C. A. Cimino, Riccardo Guidotti:
Interpretable Machine Learning for Oral Lesion Diagnosis Through Prototypical Instances Identification. DS (2) 2024: 316-331 - [c20]Mattia Bruscia, Graziano A. Manduzio, Federico A. Galatolo, Mario G. C. A. Cimino, Alberto Greco, Lorenzo Cominelli, Enzo Pasquale Scilingo:
An Overview On Large Language Models Across Key Domains: A Systematic Review. MetroXRAINE 2024: 125-130 - [i8]Graziano A. Manduzio, Federico A. Galatolo, Mario G. C. A. Cimino, Enzo Pasquale Scilingo, Lorenzo Cominelli:
Improving Small-Scale Large Language Models Function Calling for Reasoning Tasks. CoRR abs/2410.18890 (2024) - 2023
- [j3]Francesco Lupi, Mario G. C. A. Cimino, Tomaz Berlec, Federico A. Galatolo, Marko Corn, Nejc Rozman, Andrea Rossi, Michele Lanzetta:
Blockchain-based Shared Additive Manufacturing. Comput. Ind. Eng. 183: 109497 (2023) - [c19]Federico A. Galatolo, Gabriele Martino, Mario G. C. A. Cimino, Chiara Ombretta Tommasi:
Dense Information Retrieval on a Latin Digital Library via LaBSE and LatinBERT Embeddings. DATA 2023: 518-523 - [c18]Giada Simionato, Federico A. Galatolo, Mario G. C. A. Cimino:
Swarms of Artificial Platelets for Emergent Hole Detection and Healing in Wireless Sensor Networks. GECCO 2023: 75-83 - [c17]Diana Orlandi, Federico A. Galatolo, Alessandro La Rosa, Mario G. C. A. Cimino, Pierfrancesco Foglia, Carolina Pagli, Cosimo Antonio Prete:
U-Nets and Multispectral Images for Detecting the Surface Water of Rivers via SAR Images. GISTAM (Selected Papers) 2023: 1-13 - [c16]Diana Orlandi, Federico A. Galatolo, Mario G. C. A. Cimino, Carolina Pagli, Nicola Perilli, Joao A. Pompeu, Itxaso Ruiz:
Using Deep Learning and Radar Backscatter for Mapping River Water Surface. GISTAM 2023: 216-221 - [c15]Gabriele Martino, Federico A. Galatolo, Mario G. C. A. Cimino, Christian Callegari:
Using Deep Learning with Attention to Detect Data Exfiltration by POS Malware. ICEIS (1) 2023: 638-648 - [c14]Federico A. Galatolo, Mario G. C. A. Cimino, Edoardo Cogotti:
TeTIm-Eval: A Novel Curated Evaluation Data Set for Comparing Text-to-Image Models. ICPRAM 2023: 590-596 - [c13]Marco Parola, Gaetano La Mantia, Federico A. Galatolo, Mario G. C. A. Cimino, Giuseppina Campisi, Olga Di Fede:
Image-Based Screening of Oral Cancer via Deep Ensemble Architecture. SSCI 2023: 1572-1578 - [i7]Federico A. Galatolo, Mario G. C. A. Cimino:
Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and Evaluation. CoRR abs/2311.15698 (2023) - 2022
- [b1]Federico Andrea Galatolo:
Efficient Information Representation and Propagation in Artificial Neural Networks. University of Pisa, Italy, 2022 - [c12]Diana Orlandi, Federico A. Galatolo, Mario G. C. A. Cimino, Alessandro La Rosa, Carolina Pagli, Nicola Perilli:
Enhancing land subsidence awareness via InSAR data and Deep Transformers. CogSIMA 2022: 98-103 - [c11]Marco Parola, Federico A. Galatolo, Matteo Torzoni, Mario G. C. A. Cimino:
Convolutional Neural Networks for Structural Damage Localization on Digital Twins. DeLTA (Selected Papers) 2022: 78-97 - [c10]Marco Parola, Federico A. Galatolo, Matteo Torzoni, Mario G. C. A. Cimino, Gigliola Vaglini:
Structural Damage Localization via Deep Learning and IoT Enabled Digital Twin. DeLTA 2022: 199-206 - [c9]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Zero-shot Mathematical Problem Solving via Generative Pre-trained Transformers. ICEIS (1) 2022: 479-483 - [c8]Alice Nannini, Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Using Deep Learning-based Object Detection to Extract Structure Information from Scanned Documents. ICEIS (1) 2022: 610-615 - [c7]Mario G. C. A. Cimino, Federico A. Galatolo, Marco Parola, Nicola Perilli, Nunziante Squeglia:
Deep Learning of Structural Changes in Historical Buildings: The Case Study of the Pisa Tower. IJCCI 2022: 396-403 - [i6]Federico A. Galatolo, Mario G. C. A. Cimino, Edoardo Cogotti:
TeTIm-Eval: a novel curated evaluation data set for comparing text-to-image models. CoRR abs/2212.07839 (2022) - 2021
- [j2]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Solving the scalarization issues of Advantage-based Reinforcement Learning algorithms. Comput. Electr. Eng. 92: 107117 (2021) - [j1]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Formal Derivation of Mesh Neural Networks with Their Forward-Only Gradient Propagation. Neural Process. Lett. 53(3): 1963-1978 (2021) - [c6]Samar Ben Ammar, Mario G. C. A. Cimino, Pierfrancesco Foglia, Federico A. Galatolo, Issam Nouiri:
Multi-objective optimization of water distribution networks via NSGA-II and Pseudo-Weights. EUC 2021: 181-186 - [c5]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Generating Images from Caption and Vice Versa via CLIP-Guided Generative Latent Space Search. IMPROVE 2021: 166-174 - [c4]Federico A. Galatolo, Mario G. C. A. Cimino, Alessandro Marincioni, Gigliola Vaglini:
Noise Boosted Neural Receptive Fields. SSCI 2021: 1-6 - [i5]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search. CoRR abs/2102.01645 (2021) - 2020
- [i4]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Solving the scalarization issues of Advantage-based Reinforcement Learning Algorithms. CoRR abs/2004.04120 (2020)
2010 – 2019
- 2019
- [c3]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Using Stigmergy as a Computational Memory in the Design of Recurrent Neural Networks. ICPRAM 2019: 830-836 - [i3]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Using stigmergy as a computational memory in the design of recurrent neural networks. CoRR abs/1903.01341 (2019) - [i2]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Formal derivation of Mesh Neural Networks with their Forward-Only gradient Propagation. CoRR abs/1905.06684 (2019) - 2018
- [c2]Federico A. Galatolo, Mario Giovanni C. A. Cimino, Gigliola Vaglini:
Using Stigmergy to Incorporate the Time into Artificial Neural Networks. MIKE 2018: 248-258 - [i1]Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini:
Using stigmergy to incorporate the time into artificial neural networks. CoRR abs/1811.10574 (2018) - 2017
- [c1]Mario G. C. A. Cimino, Federico A. Galatolo, Alessandro Lazzeri, Witold Pedrycz, Gigliola Vaglini:
Spikiness Assessment of Term Occurrences in Microblogs: An Approach based on Computational Stigmergy. ICPRAM 2017: 731-737
Coauthor Index
aka: Mario Giovanni C. A. Cimino
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