Bridging the gap between Natural and Medical Images through Deep Colorization. - Lia Morra; Luca Piano; Fabrizio Lamberti; Tatiana Tommasi (ICPR, 2020)

Detecting Drift in Deep Learning: A Methodology Primer. - Luca Piano; Fabio Garcea; Valentina Gatteschi; Fabrizio Lamberti; Lia Morra (IT Prof., 2022)

Toward a Realistic Benchmark for Out-of-Distribution Detection. - Pietro Recalcati; Fabio Garcea; Luca Piano; Fabrizio Lamberti; Lia Morra (DSAA, 2023)

Designing Logic Tensor Networks for Visual Sudoku Puzzle Classification. - Lia Morra; Alberto Azzari; Letizia Bergamasco; Marco Braga; Luigi Capogrosso; Federico Delrio; Giuseppe Di Giacomo; Simone Eiraudo; Giorgia Ghione; Rocco Giudice; Alkis Koudounas; Luca Piano; et al. (NeSy, 2023)

Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification. - Luca Piano; Filippo Gabriele Pratticò; Alessandro Sebastian Russo; Lorenzo Lanari; Lia Morra; Fabrizio Lamberti (WACV, 2023)

Harnessing Foundation Models for Image Anonymization. - Luca Piano; Pietro Basci; Fabrizio Lamberti; Lia Morra (GEM, 2024)

Enhancing Neuro-Symbolic Integration with Focal Loss: A Study on Logic Tensor Networks. - Luca Piano; Francesco Manigrasso; Alessandro Sebastian Russo; Lia Morra (NeSy (2), 2024)

Latent Diffusion Models for Attribute-Preserving Image Anonymization. - Luca Piano; Pietro Basci; Fabrizio Lamberti; Lia Morra (CoRR, 2024)

For a semiotic AI: Bridging computer vision and visual semiotics for computational observation of large scale facial image archives. - Lia Morra; Antonio Santangelo; Pietro Basci; Luca Piano; Fabio Garcea; Fabrizio Lamberti; Massimo Leone (Comput. Vis. Image Underst., 2024)

Drift Detection for Black-Box Deep Learning Models. - Luca Piano; Fabio Garcea; Andrea Cavallone; Ignacio Aparicio Vazquez; Lia Morra; Fabrizio Lamberti (IT Prof., 2024)