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

J. dos Santos Cardoso

dblp:72/7052 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-author

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.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%

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

TopicWeightPapersLastEvidence papers
Audio and music processing
music information retrieval
0.112009
Staff Detection with Stable Paths · IEEE Trans. Pattern Anal. Mach. Intell. 2009
Audio and music processing › music information retrieval
optical music recognition
0.112009
Staff Detection with Stable Paths · IEEE Trans. Pattern Anal. Mach. Intell. 2009

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

stable path detection · 0.1
YearPublicationVenuePosition
2009 Staff Detection with Stable Paths
abstract
The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms.
J. dos Santos Cardoso, Artur Capela, Ana Rebelo, Carlos Guedes, J. Pinto da Costa
IEEE Trans. Pattern Anal. Mach. Intell.1