Demo Data from SIGIR 2026 / reviewers in the wild / expert
Gennaro Petraglia
dblp:12/408
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 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 |
Multimedia analysis and retrieval · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia analysis and retrieval › image retrieval
content-based image retrieval |
0.0 | 1 | 2001 | Virtual Images for Similarity Retrieval in Image Databases · IEEE Trans. Knowl. Data Eng. 2001 |
Multimedia analysis and retrieval
similarity search |
0.0 | 1 | 2001 | Virtual Images for Similarity Retrieval in Image Databases · IEEE Trans. Knowl. Data Eng. 2001 |
Multimedia analysis and retrieval › image analysis › scene analysis
spatial relation modeling |
0.0 | 1 | 2001 | Virtual Images for Similarity Retrieval in Image Databases · IEEE Trans. Knowl. Data Eng. 2001 |
Methods — techniques the papers use, named apart from their topics
virtual image indexing · 0.0spatial relation representation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | The Virtual Image in Streaming Video Indexing
Piera Palma, Luca Petraglia, Gennaro Petraglia |
Dublin Core Conference | 3 |
| 2001 | Virtual Images for Similarity Retrieval in Image DatabasesabstractWe introduce the virtual image, an iconic index suited for pictorial information access in a pictorial database, and a similarity retrieval approach based on virtual images to perform content-based retrieval. A virtual image represents the spatial information contained in a real image in explicit form by means of a set of spatial relations. This is useful to efficiently compute the similarity between a query and an image in the database. We also show that virtual images support real-world applications that require translation, reflection, and/or rotation invariance of image representation. Gennaro Petraglia, Monica Sebillo, Maurizio Tucci, Genny Tortora |
IEEE Trans. Knowl. Data Eng. | 1 |