collaborators

7 papers

cs.CV2026

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

Luca Ciampi, Gabriele Lagani, Giuseppe Amato +1

Supervised deep learning for semantic segmentation has achieved excellent results in accurately identifying anatomical and pathological structures in medical images. However, it of…

cs.CV2026

Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computing

Luca Ciampi, Ludovico Iannello, Fabrizio Tonelli +4

In this paper, we present a neuro-inspired approach to reservoir computing (RC) in which a network of in vitro cultured cortical neurons serves as the physical reservoir. Rather th…

cs.NE2025

From Neural Activity to Computation: Biological Reservoirs for Pattern Recognition in Digit Classification

Ludovico Iannello, Luca Ciampi, Fabrizio Tonelli +5

In this paper, we present a biologically grounded approach to reservoir computing (RC), in which a network of cultured biological neurons serves as the reservoir substrate. This sy…

cs.NE2025

From Neurons to Computation: Biological Reservoir Computing for Pattern Recognition

Ludovico Iannello, Luca Ciampi, Gabriele Lagani +6

In this paper, we introduce a paradigm for reservoir computing (RC) that leverages a pool of cultured biological neurons as the reservoir substrate, creating a biological reservoir…

cs.CV2025

CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro +1

In this paper, we introduce a deep learning solution for video activity recognition that leverages an innovative combination of convolutional layers with a linear-complexity attent…

cs.CV2025

Comparison of Different Deep Neural Network Models in the Cultural Heritage Domain

Teodor Boyadzhiev, Gabriele Lagani, Luca Ciampi +2

The integration of computer vision and deep learning is an essential part of documenting and preserving cultural heritage, as well as improving visitor experiences. In recent years…