Gabriele Lagani

29 papers B 1C 1Journal 17Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computing. CoRR Luca Ciampi, Ludovico Iannello, Fabrizio Tonelli, Gabriele Lagani, Angelo Di Garbo, Federico Cremisi, Giuseppe Amato
2025	J	`jnl`	CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge. CoRR Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2025	J	`jnl`	Comparison of Different Deep Neural Network Models in the Cultural Heritage Domain. CoRR Teodor Boyadzhiev, Gabriele Lagani, Luca Ciampi, Giuseppe Amato, Krassimira Ivanova
2025	—	`conf`	From Neural Activity to Computation: Biological Reservoirs for Pattern Recognition in Digit Classification. ICCVW Ludovico Iannello, Luca Ciampi, Fabrizio Tonelli, Gabriele Lagani, Lucio Maria Calcagnile, Federico Cremisi, Angelo Di Garbo, Giuseppe Amato
2025	J	`jnl`	From Neural Activity to Computation: Biological Reservoirs for Pattern Recognition in Digit Classification. CoRR Ludovico Iannello, Luca Ciampi, Fabrizio Tonelli, Gabriele Lagani, Lucio Maria Calcagnile, Federico Cremisi, Angelo Di Garbo, Giuseppe Amato
2025	J	`jnl`	From Neurons to Computation: Biological Reservoir Computing for Pattern Recognition. CoRR Ludovico Iannello, Luca Ciampi, Gabriele Lagani, Fabrizio Tonelli, Eleonora Crocco, Lucio Maria Calcagnile, Angelo Di Garbo, Federico Cremisi, Giuseppe Amato
2025	J	`jnl`	Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training. CoRR Luca Ciampi, Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi
2024	—	`conf`	A Biologically-Inspired Approach to Biomedical Image Segmentation. ECCV Workshops (14) Luca Ciampi, Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi
2024	J	`jnl`	Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging. CoRR Luca Ciampi, Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi
2024	—	`conf`	CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge. ECCV Workshops (11) Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2024	J	`jnl`	Scalable bio-inspired training of Deep Neural Networks with FastHebb. Neurocomputing Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Hannes Fassold, Giuseppe Amato
2023	—	`conf`	AIMH Lab for a Susteinable Bio-Inspired AI. Ital-IA Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2023	—	`conf`	Scaling Bio-Inspired Neural Features to Real-World Image Retrieval Problems. SEBD Gabriele Lagani
2023	J	`jnl`	Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey. CoRR Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2023	J	`jnl`	Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey. CoRR Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2022	J	`jnl`	Comparing the performance of Hebbian against backpropagation learning using convolutional neural networks. Neural Comput. Appl. Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2022	C	`conf`	Deep Features for CBIR with Scarce Data using Hebbian Learning. CBMI Gabriele Lagani, Davide Bacciu, Claudio Gallicchio, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2022	J	`jnl`	Deep Features for CBIR with Scarce Data using Hebbian Learning. CoRR Gabriele Lagani, Davide Bacciu, Claudio Gallicchio, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2022	B	`conf`	FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level. SISAP Gabriele Lagani, Claudio Gennaro, Hannes Fassold, Giuseppe Amato
2022	J	`jnl`	FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level. CoRR Gabriele Lagani, Claudio Gennaro, Hannes Fassold, Giuseppe Amato
2022	—	`conf`	Recent Advancements on Bio-Inspired Hebbian Learning for Deep Neural Networks. SEBD Gabriele Lagani
2021	—	`conf`	Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation. NER Gabriele Lagani, Raffaele Mazziotti, Fabrizio Falchi, Claudio Gennaro, Guido Marco Cicchini, Tommaso Pizzorusso, Federico Cremisi, Giuseppe Amato
2021	—	`conf`	Evaluating Hebbian Learning in a Semi-supervised Setting. LOD Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2021	J	`jnl`	Hebbian Semi-Supervised Learning in a Sample Efficiency Setting. CoRR Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2021	J	`jnl`	Hebbian semi-supervised learning in a sample efficiency setting. Neural Networks Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2021	—	`conf`	Training Convolutional Neural Networks with Competitive Hebbian Learning Approaches. LOD Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
2020	J	`jnl`	Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation. CoRR Gabriele Lagani, Raffaele Mazziotti, Fabrizio Falchi, Claudio Gennaro, Guido Marco Cicchini, Tommaso Pizzorusso, Federico Cremisi, Giuseppe Amato
2020	J	`jnl`	Training Convolutional Neural Networks With Hebbian Principal Component Analysis. CoRR Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro
2019	—	`conf`	Hebbian Learning Meets Deep Convolutional Neural Networks. ICIAP (1) Giuseppe Amato, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, Gabriele Lagani