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Gabriele Lagani
Gabriele Lagani
ISTI-CNR, Pisa
Verified email at isti.cnr.it - Homepage
Title
Cited by
Cited by
Year
Hebbian learning meets deep convolutional neural networks
G Amato, F Carrara, F Falchi, C Gennaro, G Lagani
Image Analysis and Processing–ICIAP 2019: 20th International Conference …, 2019
672019
Hebbian Semi-Supervised Learning in a Sample Efficiency Setting
G Lagani, F Fabrizio, C Gennaro, G Amato
Neural Networks 143, 719-731, 2021
342021
Comparing the performance of Hebbian against backpropagation learning using convolutional neural networks
G Lagani, F Falchi, C Gennaro, G Amato
Neural Computing and Applications 34 (8), 6503-6519, 2022
292022
Hebbian learning algorithms for training convolutional neural networks
G Lagani
142019
Evaluating hebbian learning in a semi-supervised setting
G Lagani, F Falchi, C Gennaro, G Amato
International Conference on Machine Learning, Optimization, and Data Science …, 2021
132021
Training convolutional neural networks with competitive hebbian learning approaches
G Lagani, F Falchi, C Gennaro, G Amato
International Conference on Machine Learning, Optimization, and Data Science …, 2021
112021
Fasthebb: Scaling hebbian training of deep neural networks to imagenet level
G Lagani, C Gennaro, H Fassold, G Amato
International Conference on Similarity Search and Applications, 251-264, 2022
92022
Spiking neural networks and bio-inspired supervised deep learning: a survey
G Lagani, F Falchi, C Gennaro, G Amato
arXiv preprint arXiv:2307.16235, 2023
82023
Deep features for cbir with scarce data using hebbian learning
G Lagani, D Bacciu, C Gallicchio, F Falchi, C Gennaro, G Amato
Proceedings of the 19th International Conference on Content-based Multimedia …, 2022
82022
Assessing pattern recognition performance of neuronal cultures through accurate simulation
G Lagani, R Mazziotti, F Falchi, C Gennaro, GM Cicchini, T Pizzorusso, ...
2021 10th International IEEE/EMBS Conference on Neural Engineering (NER …, 2021
82021
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey
G Lagani, F Falchi, C Gennaro, G Amato
arXiv preprint arXiv:2307.16236, 2023
32023
Bio-Inspired Approaches for Deep Learning: From Spiking Neural Networks to Hebbian Plasticity
G Lagani
32023
Scalable bio-inspired training of deep neural networks with FastHebb
G Lagani, F Falchi, C Gennaro, H Fassold, G Amato
Neurocomputing, 127867, 2024
12024
AIMH Lab for a Susteinable Bio-Inspired AI.
G Lagani, F Falchi, C Gennaro, G Amato
Ital-IA, 575-584, 2023
12023
Scaling Bio-Inspired Neural Features to Real-World Image Retrieval Problems.
G Lagani
SEBD, 711-717, 2023
12023
AIMH Research Activities 2022
N Aloia, G Amato, V Bartalesi, F Benedetti, P Bolettieri, D Cafarelli, ...
CNR, 2022
12022
Recent Advancements on Bio-Inspired Hebbian Learning for Deep Neural Networks.
G Lagani
SEBD, 610-615, 2022
12022
Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging
L Ciampi, G Lagani, G Amato, F Falchi
arXiv preprint arXiv:2412.03192, 2024
2024
AIMIR Research Activities 2019
G Amato, P Bolettieri, F Carrara, L Ciampi, M Di Benedetto, F Debole, ...
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