Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from EDBT 2026 / reviewers in the wild / expert

Federico Cremisi

dblp:281/8541 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Deep learning architectures and training · 50% Image recognition and object detection · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Deep learning architectures and training › recurrent neural network
reservoir computing		 1.012026
Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computing · Int. J. Comput. Vis. 2026
Computer vision › Image recognition and object detection › object recognition
visual pattern recognition		 1.012026
Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computing · Int. J. Comput. Vis. 2026

Methods — techniques the papers use, named apart from their topics

reservoir computing · 1.0
YearPublicationVenuePosition
2026 Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computing
Luca Ciampi, Ludovico Iannello, Fabrizio Tonelli, Gabriele Lagani, Angelo Di Garbo, Federico Cremisi, Giuseppe Amato 0001
 Int. J. Comput. Vis.6