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ORCIDDaniele Loiacono
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2020 – today
- 2024
[c67]Elio Sasso, Daniele Loiacono, Pier Luca Lanzi
:
A Tool for the Procedural Generation of Shaders Using Interactive Evolutionary Algorithms. GEM 2024: 1-4- [c66]Ricardo Coimbra Brioso, Damiano Dei, Nicola Lambri, Pietro Mancosu, Marta Scorsetti, Daniele Loiacono:
Investigating Gender Bias in Lymph-Node Segmentation with Anatomical Priors. FAIMI/EPIMI@MICCAI 2024: 151-160 - [i16]Ricardo Coimbra Brioso, Damiano Dei, Nicola Lambri, Daniele Loiacono, Pietro Mancosu, Marta Scorsetti:
Deep Learning-Based Auto-Segmentation of Planning Target Volume for Total Marrow and Lymph Node Irradiation. CoRR abs/2402.06494 (2024) - [i15]Leonardo Crespi, Samuele Camnasio, Damiano Dei, Nicola Lambri, Pietro Mancosu, Marta Scorsetti, Daniele Loiacono:
Leveraging Multimodal CycleGAN for the Generation of Anatomically Accurate Synthetic CT Scans from MRIs. CoRR abs/2407.10888 (2024) - [i14]Ricardo Coimbra Brioso, Damiano Dei, Nicola Lambri, Pietro Mancosu, Marta Scorsetti, Daniele Loiacono:
Investigating Gender Bias in Lymph-node Segmentation with Anatomical Priors. CoRR abs/2409.15888 (2024) - 2023
- [j16]Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono:
An analysis of DOOM level generation using Generative Adversarial Networks. Entertain. Comput. 46: 100549 (2023) - [j15]Erica Stella, Isabella Agosti, Nicoletta Di Blas, Marco Finazzi, Pier Luca Lanzi, Daniele Loiacono:
A virtual reality classroom to teach and explore crystal solid state structures. Multim. Tools Appl. 82(5): 6993-7016 (2023) - [c65]Ricardo Coimbra Brioso, Damiano Dei, Ciro Franzese, Nicola Lambri, Daniele Loiacono, Pietro Mancosu, Marta Scorsetti:
Segmentation of Planning Target Volume in CT Series for Total Marrow Irradiation Using U-Net. CBMS 2023: 477-482 - [c64]Leonardo Crespi, Paolo Roncaglioni, Damiano Dei, Ciro Franzese, Nicola Lambri, Daniele Loiacono, Pietro Mancosu, Marta Scorsetti:
Ensemble Methods for Multi-Organ Segmentation in CT series. CBMS 2023: 505-510 - [c63]Leonardo Crespi, Mattia Portanti, Daniele Loiacono:
Comparing Adversarial and Supervised Learning for Organs at Risk Segmentation in CT images. CBMS 2023: 567-572 - [c62]Pier Luca Lanzi, Daniele Loiacono:
ChatGPT and Other Large Language Models as Evolutionary Engines for Online Interactive Collaborative Game Design. GECCO 2023: 1383-1390 - [i13]Pier Luca Lanzi, Daniele Loiacono:
ChatGPT and Other Large Language Models as Evolutionary Engines for Online Interactive Collaborative Game Design. CoRR abs/2303.02155 (2023) - [i12]Leonardo Crespi, Mattia Portanti, Daniele Loiacono:
Comparing Adversarial and Supervised Learning for Organs at Risk Segmentation in CT images. CoRR abs/2303.17941 (2023) - [i11]Leonardo Crespi, Paolo Roncaglioni, Damiano Dei, Ciro Franzese, Nicola Lambri, Daniele Loiacono, Pietro Mancosu, Marta Scorsetti:
Ensemble Methods for Multi-Organ Segmentation in CT Series. CoRR abs/2303.17956 (2023) - [i10]Ricardo Coimbra Brioso, Damiano Dei, Ciro Franzese, Nicola Lambri, Daniele Loiacono, Pietro Mancosu, Marta Scorsetti:
Segmentation of Planning Target Volume in CT Series for Total Marrow Irradiation Using U-Net. CoRR abs/2304.02353 (2023) - [i9]Elio Sasso, Daniele Loiacono, Pier Luca Lanzi:
A Tool for the Procedural Generation of Shaders using Interactive Evolutionary Algorithms. CoRR abs/2312.17587 (2023) - 2022
- [j14]Alper Kanyilmaz, Patricia Raquel Navarro Tichell, Daniele Loiacono:
A genetic algorithm tool for conceptual structural design with cost and embodied carbon optimization. Eng. Appl. Artif. Intell. 112: 104711 (2022) - [c61]Maria Francesca Costabile, Giuseppe Desolda, Giovanni Dimauro, Rosa Lanzilotti, Daniele Loiacono, Maristella Matera, Massimo Zancanaro:
A human-centric AI-driven framework for exploring large and complex datasets. CoPDA@AVI 2022: 9-13 - [c60]Leonardo Crespi, Daniele Loiacono, Pierandrea Sartori:
Are 3D better than 2D Convolutional Neural Networks for Medical Imaging Semantic Segmentation? IJCNN 2022: 1-8 - [i8]Pier Luca Lanzi, Daniele Loiacono, Alberto Arosio, Dorian Bucur, Davide Caio, Luca Capecchi, Maria Giulietta Cappelletti, Lorenzo Carnaghi, Marco Giuseppe Caruso, Valerio Ceraudo, Luca Contato, Luca Cornaggia, Christian Costanza, Tommaso Grilli, Sumero Lira, Luca Marchetti, Giulia Olivares, Barbara Pagano, Davide Pons, Michele Pirovano, Valentina Tosto:
One Pixel, One Interaction, One Game: An Experiment in Minimalist Game Design. CoRR abs/2207.03827 (2022) - 2021
- [c59]Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono, Luca Nassano:
Image Embedding and Model Ensembling for Automated Chest X-Ray Interpretation. IJCNN 2021: 1-8 - [c58]Leonardo Crespi, Daniele Loiacono, Arturo Chiti:
Chest X-Rays Image Classification from $\beta{-}$ Variational Autoencoders Latent Features. SSCI 2021: 1-8 - [i7]Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono, Luca Nassano:
Image Embedding and Model Ensembling for Automated Chest X-Ray Interpretation. CoRR abs/2105.02966 (2021) - [i6]Leonardo Crespi, Daniele Loiacono, Arturo Chiti:
Chest X-Rays Image Classification from beta-Variational Autoencoders Latent Features. CoRR abs/2109.14760 (2021) - [i5]Edoardo Giacomello, Michele Cataldo, Daniele Loiacono, Pier Luca Lanzi:
Distributed Learning Approaches for Automated Chest X-Ray Diagnosis. CoRR abs/2110.01474 (2021) - 2020
- [j13]Camilla Colombo, Nicoletta Di Blas, Ioannis Gkolias, Pier Luca Lanzi, Daniele Loiacono, Erica Stella:
An Educational Experience to Raise Awareness About Space Debris. IEEE Access 8: 85162-85178 (2020) - [c57]Pier Luca Lanzi, Daniele Loiacono:
Asking Students to Do All the Work: An Analysis of a Fully Peer-Assessed Course on Game Design and Development. FDG 2020: 94:1-94:10 - [c56]Edoardo Giacomello, Daniele Loiacono, Luca T. Mainardi:
Brain MRI Tumor Segmentation with Adversarial Networks. IJCNN 2020: 1-8 - [c55]Emilio Capo, Daniele Loiacono:
Short-Term Trajectory Planning in TORCS using Deep Reinforcement Learning. SSCI 2020: 2327-2334 - [c54]Umberto Picariello, Daniele Loiacono, Fabio Mosca, Pier Luca Lanzi:
A Framework to Create Collaborative Games for Team Building using Procedural Content Generation. SSCI 2020: 2365-2372 - [c53]Emanuel Alogna, Edoardo Giacomello, Daniele Loiacono:
Brain Magnetic Resonance Imaging Generation using Generative Adversarial Networks. SSCI 2020: 2528-2535
2010 – 2019
- 2019
- [j12]Daniele Loiacono, Luca Arnaboldi:
Multiobjective Evolutionary Map Design for Cube 2: Sauerbraten. IEEE Trans. Games 11(1): 36-47 (2019) - [c52]Marco Ballabio, Daniele Loiacono:
Heuristics for Placing the Spawn Points in Multiplayer First Person Shooters. CoG 2019: 1-8 - [c51]Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono:
Searching the Latent Space of a Generative Adversarial Network to Generate DOOM Levels. CoG 2019: 1-8 - [i4]Edoardo Giacomello, Daniele Loiacono, Luca T. Mainardi:
Transfer Brain MRI Tumor Segmentation Models Across Modalities with Adversarial Networks. CoRR abs/1910.02717 (2019) - 2018
- [c50]Antonio Umberto Aramini, Pier Luca Lanzi, Daniele Loiacono:
An Integrated Framework for AI Assisted Level Design in 2D Platformers. GEM 2018: 1-9 - [c49]Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono:
DOOM Level Generation Using Generative Adversarial Networks. GEM 2018: 316-323 - [c48]Filippo Agalbato, Daniele Loiacono:
Robo3: A Puzzle Game to Learn Coding. GEM 2018: 359-366 - [i3]Antonio Umberto Aramini, Pier Luca Lanzi, Daniele Loiacono:
An Integrated Framework for AI Assisted Level Design in 2D Platformers. CoRR abs/1804.09153 (2018) - [i2]Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono:
DOOM Level Generation using Generative Adversarial Networks. CoRR abs/1804.09154 (2018) - 2017
- [c47]Daniele Loiacono, Luca Arnaboldi:
Fight or flight: Evolving maps for cube 2 to foster a fleeing behavior. CIG 2017: 199-206 - 2015
- [j11]Luigi Cardamone, Pier Luca Lanzi, Daniele Loiacono:
TrackGen: An interactive track generator for TORCS and Speed-Dreams. Appl. Soft Comput. 28: 550-558 (2015) - [j10]Pier Luca Lanzi, Daniele Loiacono:
XCSF with tile coding in discontinuous action-value landscapes. Evol. Intell. 8(2-3): 117-132 (2015) - [c46]Daniele Gravina, Daniele Loiacono:
Procedural weapons generation for unreal tournament III. GEM 2015: 1-8 - [c45]Michele Pirovano, Renato Mainetti, Daniele Loiacono:
Volcano: An interactive sword generator. GEM 2015: 1-8 - 2014
- [j9]Daniele Loiacono:
Gene I. Sher: Handbook of neuroevolution through Erlang - Springer, 2013, ISBN: 978-1461444626, pp 831, $189. Genet. Program. Evolvable Mach. 15(1): 109-110 (2014) - [j8]Daniele Loiacono, Moshe Sipper:
Special issue on GECCO competitions. Genet. Program. Evolvable Mach. 15(4): 375-377 (2014) - [c44]Luca Galli, Pier Luca Lanzi, Daniele Loiacono:
Applying data mining to extract design patterns from Unreal Tournament levels. CIG 2014: 1-8 - [c43]Pier Luca Lanzi, Daniele Loiacono, Riccardo Stucchi:
Evolving maps for match balancing in first person shooters. CIG 2014: 1-8 - 2013
- [j7]Luigi Cardamone, Pier Luca Lanzi, Daniele Loiacono, Enrique Onieva:
Advanced overtaking behaviors for blocking opponents in racing games using a fuzzy architecture. Expert Syst. Appl. 40(16): 6447-6458 (2013) - [c42]Pier Luca Lanzi, Daniele Loiacono, Emanuele Parini, Federico Sannicoló, Davide Jones, Claudio Scamporlino:
Tuning mobile game design using data mining. IGIC 2013: 122-129 - [c41]Daniele Loiacono, Mike Preuss:
Computational intelligence and games. GECCO (Companion) 2013: 957-978 - [p1]Georgios N. Yannakakis, Pieter Spronck, Daniele Loiacono, Elisabeth André:
Player Modeling. Artificial and Computational Intelligence in Games 2013: 45-59 - [i1]Daniele Loiacono, Luigi Cardamone, Pier Luca Lanzi:
Simulated Car Racing Championship: Competition Software Manual. CoRR abs/1304.1672 (2013) - 2012
- [j6]Daniele Loiacono, Albert Orriols-Puig, Ryan J. Urbanowicz:
Special issue on advances in learning classifier systems. Evol. Intell. 5(2): 57-58 (2012) - [c40]Daniele Loiacono:
Learning, evolution and adaptation in racing games. Conf. Computing Frontiers 2012: 277-284 - [c39]Matteo Botta, Vincenzo Gautieri, Daniele Loiacono, Pier Luca Lanzi:
Evolving the optimal racing line in a high-end racing game. CIG 2012: 108-115 - [c38]Daniele Loiacono, Mike Preuß:
Computational intelligence in games. GECCO (Companion) 2012: 1139-1140 - 2011
- [j5]Daniele Loiacono, Luigi Cardamone, Pier Luca Lanzi:
Automatic Track Generation for High-End Racing Games Using Evolutionary Computation. IEEE Trans. Comput. Intell. AI Games 3(3): 245-259 (2011) - [c37]Luigi Cardamone, Antonio Caiazzo, Daniele Loiacono, Pier Luca Lanzi:
Transfer of driving behaviors across different racing games. CIG 2011: 227-234 - [c36]Luca Galli, Daniele Loiacono, Luigi Cardamone, Pier Luca Lanzi:
A cheating detection framework for Unreal Tournament III: A machine learning approach. CIG 2011: 266-272 - [c35]Daniele Loiacono:
Fast prediction computation in learning classifier systems using CUDA. GECCO (Companion) 2011: 169-170 - [c34]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
Interactive evolution for the procedural generation of tracks in a high-end racing game. GECCO 2011: 395-402 - 2010
- [j4]Daniele Loiacono, Pier Luca Lanzi, Julian Togelius, Enrique Onieva, David A. Pelta, Martin V. Butz, Thies D. Lönneker, Luigi Cardamone, Diego Perez Liebana, Yago Sáez, Mike Preuss, Jan Quadflieg:
The 2009 Simulated Car Racing Championship. IEEE Trans. Comput. Intell. AI Games 2(2): 131-147 (2010) - [j3]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
Learning to Drive in the Open Racing Car Simulator Using Online Neuroevolution. IEEE Trans. Comput. Intell. AI Games 2(3): 176-190 (2010) - [c33]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
Applying cooperative coevolution to compete in the 2009 TORCS Endurance World Championship. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c32]Daniele Loiacono, Alessandro Prete, Pier Luca Lanzi, Luigi Cardamone:
Learning to overtake in TORCS using simple reinforcement learning. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c31]Enrique Onieva, Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
Overtaking opponents with blocking strategies using fuzzy logic. CIG 2010: 123-130 - [c30]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi, Alessandro Pietro Bardelli:
Searching for the optimal racing line using genetic algorithms. CIG 2010: 388-394
2000 – 2009
- 2009
- [c29]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
On-line neuroevolution applied to The Open Racing Car Simulator. IEEE Congress on Evolutionary Computation 2009: 2622-2629 - [c28]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
Learning drivers for TORCS through imitation using supervised methods. CIG 2009: 148-155 - [c27]Luca Galli, Daniele Loiacono, Pier Luca Lanzi:
Learning a context-aware weapon selection policy for Unreal Tournament III. CIG 2009: 310-316 - [c26]Daniele Loiacono, Julian Togelius, Pier Luca Lanzi:
Simulated car racing. CIG 2009 - [c25]Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:
Evolving competitive car controllers for racing games with neuroevolution. GECCO 2009: 1179-1186 - [c24]Pier Luca Lanzi, Daniele Loiacono:
Speeding Up Matching in Learning Classifier Systems Using CUDA. IWLCS 2009: 1-20 - [c23]Daniele Loiacono, Pier Luca Lanzi:
Recursive Least Squares and Quadratic Prediction in Continuous Multistep Problems. IWLCS 2009: 70-86 - 2008
- [c22]Christian Pilato, Daniele Loiacono, Fabrizio Ferrandi, Pier Luca Lanzi, Donatella Sciuto:
High-level synthesis with multi-objective genetic algorithm: A comparative encoding analysis. IEEE Congress on Evolutionary Computation 2008: 3334-3341 - [c21]Daniele Loiacono, Pier Luca Lanzi:
Computed prediction in binary multistep problems. IEEE Congress on Evolutionary Computation 2008: 3350-3357 - [c20]Pier Luca Lanzi, Daniele Loiacono, Matteo Zanini:
Evolving classifier ensembles with voting predictors. IEEE Congress on Evolutionary Computation 2008: 3760-3767 - [c19]Daniele Loiacono, Julian Togelius, Pier Luca Lanzi, Leonard Kinnaird-Heether, Simon M. Lucas, Matt Simmerson, Diego Perez Liebana, Robert G. Reynolds, Yago Sáez:
The WCCI 2008 simulated car racing competition. CIG 2008: 119-126 - [c18]Daniele Loiacono, Pier Luca Lanzi:
Tile Coding Based on Hyperplane Tiles. EWRL 2008: 179-190 - [c17]Martin V. Butz, Pier Luca Lanzi, Xavier Llorà, Daniele Loiacono:
An analysis of matching in learning classifier systems. GECCO 2008: 1349-1356 - [c16]Daniele Loiacono, Pier Luca Lanzi:
Recursive least squares and quadratic prediction in continuous multistep problems. GECCO (Companion) 2008: 1985-1992 - [c15]Fabrizio Ferrandi, Pier Luca Lanzi, Daniele Loiacono, Christian Pilato, Donatella Sciuto:
A Multi-objective Genetic Algorithm for Design Space Exploration in High-Level Synthesis. ISVLSI 2008: 417-422 - 2007
- [j2]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
Generalization in the XCSF Classifier System: Analysis, Improvement, and Extension. Evol. Comput. 15(2): 133-168 (2007) - [j1]Fabio Dercole, Daniele Loiacono, Sergio Rinaldi:
Synchronization in Ecological Networks: a Byproduct of Darwinian Evolution? Int. J. Bifurc. Chaos 17(7): 2435-2446 (2007) - [c14]Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi:
Support vector machines for computing action mappings in learning classifier systems. IEEE Congress on Evolutionary Computation 2007: 2141-2148 - [c13]Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi:
Support vector regression for classifier prediction. GECCO 2007: 1806-1813 - [c12]Pier Luca Lanzi, Daniele Loiacono:
Classifier systems that compute action mappings. GECCO 2007: 1822-1829 - [c11]Daniele Loiacono, Jan Drugowitsch, Alwyn Barry, Pier Luca Lanzi:
Analysis and Improvements of the Classifier Error Estimate in XCSF. IWLCS 2007: 117-135 - [c10]Pier Luca Lanzi, Daniele Loiacono, Matteo Zanini:
Evolving Classifiers Ensembles with Heterogeneous Predictors. IWLCS 2007: 218-234 - 2006
- [c9]Pier Luca Lanzi, Daniele Loiacono:
XCSF with Neural Prediction. IEEE Congress on Evolutionary Computation 2006: 2270-2276 - [c8]Pier Luca Lanzi, Daniele Loiacono:
Standard and averaging reinforcement learning in XCS. GECCO 2006: 1489-1496 - [c7]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
Classifier prediction based on tile coding. GECCO 2006: 1497-1504 - [c6]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
Prediction update algorithms for XCSF: RLS, Kalman filter, and gain adaptation. GECCO 2006: 1505-1512 - 2005
- [c5]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
XCS with computed prediction for the learning of Boolean functions. Congress on Evolutionary Computation 2005: 588-595 - [c4]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
XCS with computed prediction in continuous multistep environments. Congress on Evolutionary Computation 2005: 2032-2039 - [c3]Daniele Loiacono, Pier Luca Lanzi:
Improving generalization in the XCSF classifier system using linear least-squares. GECCO Workshops 2005: 374-377 - [c2]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
Extending XCSF beyond linear approximation. GECCO 2005: 1827-1834 - [c1]Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
XCS with computed prediction in multistep environments. GECCO 2005: 1859-1866
Coauthor Index
[c67] [j16] [j15] [c62] [i13] [i9] [i8] [c59] [i7] [i5] [j13] [c57] [c54] [c51] [c50] [c49] [i3] [i2] [j11] [j10] [c44] [c43] [j7] [c42] [i1] [c39] [j5] [c37] [c36] [c34] [j4] [j3] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [j2] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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last updated on 2024-11-04 21:42 CET by the dblp team
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