24 citations · 30 across the 6 of their papers we have counts for
7 papers
QuantFormer: Learning to Quantize for Neural Activity Forecasting in Mouse Visual Cortex
Salvatore Calcagno, Isaak Kavasidis, Simone Palazzo +8
Understanding complex animal behaviors hinges on deciphering the neural activity patterns within brain circuits, making the ability to forecast neural activity crucial for developi…
BioTrak: A Blockchain-based Platform for Food Chain Logistics Traceability
A. Spitalleri, I. Kavasidis, V. Cartelli +5
The food supply chain, following its globalization, has become very complex. Such complexities, introduce factors that influence adversely the quality of intermediate and final pro…
An Explainable AI System for Automated COVID-19 Assessment and Lesion Categorization from CT-scans
Matteo Pennisi, Isaak Kavasidis, Concetto Spampinato +12
COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pandemic outbreak all over the world with exponential increasing of confirmed cases and, unfortunately, deaths. I…
Correct block-design experiments mitigate temporal correlation bias in EEG classification
Simone Palazzo, Concetto Spampinato, Joseph Schmidt +3
It is argued in [1] that [2] was able to classify EEG responses to visual stimuli solely because of the temporal correlation that exists in all EEG data and the use of a block desi…
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features
Simone Palazzo, Concetto Spampinato, Isaak Kavasidis +3
This work presents a novel method of exploring human brain-visual representations, with a view towards replicating these processes in machines. The core idea is to learn plausible…
A Saliency-based Convolutional Neural Network for Table and Chart Detection in Digitized Documents
I. Kavasidis, S. Palazzo, C. Spampinato +4
Deep Convolutional Neural Networks (DCNNs) have recently been applied successfully to a variety of vision and multimedia tasks, thus driving development of novel solutions in sever…
Deep Learning Human Mind for Automated Visual Classification
Concetto Spampinato, Simone Palazzo, Isaak Kavasidis +3
What if we could effectively read the mind and transfer human visual capabilities to computer vision methods? In this paper, we aim at addressing this question by developing the fi…