5 citations · 11 across the 13 of their papers we have counts for
6 papers · 1 filter
Stochastic Coherence Over Attention Trajectory For Continuous Learning In Video Streams
Matteo Tiezzi, Simone Marullo, Lapo Faggi +3
Devising intelligent agents able to live in an environment and learn by observing the surroundings is a longstanding goal of Artificial Intelligence. From a bare Machine Learning p…
Evaluating Continual Learning Algorithms by Generating 3D Virtual Environments
Enrico Meloni, Alessandro Betti, Lapo Faggi +3
Continual learning refers to the ability of humans and animals to incrementally learn over time in a given environment. Trying to simulate this learning process in machines is a ch…
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…
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…
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…
Convolutional Networks in Visual Environments
Alessandro Betti, Marco Gori
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…