53 citations · 57 across the 4 of their papers we have counts for
6 papers · 1 filter
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…
Domain Adaptation for Outdoor Robot Traversability Estimation from RGB data with Safety-Preserving Loss
Simone Palazzo, Dario C. Guastella, Luciano Cantelli +5
Being able to estimate the traversability of the area surrounding a mobile robot is a fundamental task in the design of a navigation algorithm. However, the task is often complex,…
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…
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos
C. Spampinato, S. Palazzo, P. D'Oro +2
Human behavior understanding in videos is a complex, still unsolved problem and requires to accurately model motion at both the local (pixel-wise dense prediction) and global (aggr…
Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network
Nasim Souly, Concetto Spampinato, Mubarak Shah
Semantic segmentation has been a long standing challenging task in computer vision. It aims at assigning a label to each image pixel and needs significant number of pixellevel anno…