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20182022
most citedNeural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

99 citations · 131 across the 15 of their papers we have counts for

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8 papers · 1 filter

cs.CV20207 cited

Gravitational Models Explain Shifts on Human Visual Attention

Dario Zanca, Marco Gori, Stefano Melacci +1

Visual attention refers to the human brain's ability to select relevant sensory information for preferential processing, improving performance in visual and cognitive tasks. It pro…

cs.CV2020

Toward Improving the Evaluation of Visual Attention Models: a Crowdsourcing Approach

Dario Zanca, Stefano Melacci, Marco Gori

Human visual attention is a complex phenomenon. A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient loca…

cs.CV2019

Learning Visual Features Under Motion Invariance

Alessandro Betti, Marco Gori, Stefano Melacci

Humans are continuously exposed to a stream of visual data with a natural temporal structure. However, most successful computer vision algorithms work at image level, completely di…

cs.CV2018

Coherence Constraints in Facial Expression Recognition

Lisa Graziani, Stefano Melacci, Marco Gori

Recognizing facial expressions from static images or video sequences is a widely studied but still challenging problem. The recent progresses obtained by deep neural architectures,…

cs.CV2018

Cognitive Action Laws: The Case of Visual Features

Alessandro Betti, Marco Gori, Stefano Melacci

This paper proposes a theory for understanding perceptual learning processes within the general framework of laws of nature. Neural networks are regarded as systems whose connectio…

cs.CV2018

Motion Invariance in Visual Environments

Alessandro Betti, Marco Gori, Stefano Melacci

The puzzle of computer vision might find new challenging solutions when we realize that most successful methods are working at image level, which is remarkably more difficult than…