Demo Data from VLDB 2026 / reviewers in the wild / expert
Luca Ghilardi
dblp:56/4836
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0005-3708-4548ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1
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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › image retrieval
shape retrieval |
0.1 | 1 | 2007 | A flexible retrieval system of shapes in binary images · SIGIR 2007 |
Methods — techniques the papers use, named apart from their topics
multifractal spectrum · 0.1fourier coefficients · 0.1contour scale space · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Meta-reinforcement learning guidance, navigation, and control for autonomous lunar landing with safe site selection
Andrea Scorsoglio, Brian Gaudet, Luca Ghilardi, Roberto Furfaro |
Neural Comput. Appl. | 3 |
| 2007 | A flexible retrieval system of shapes in binary imagesabstractThis poster overviews the main characteristics of a flexible retrieval systems of shapes present in binary images and discusses some evaluation results. The system applies multiple indexing criteria of the shapes synthesizing distinct characteristics such as global features of the objects contour (Fourier Coefficients), boundary irregularities (Multifractal Spectrum), presence of concavities and convexities on the boundary (Contour Scale Space distribution). The system is flexible since it allows customizing the retrieval function to fit an application need. The query is a binary image containing the desired shape and a set of parameters specifying the distinct importance of the shape characteristics that must be taken into account to evaluate the relevance of the retrieved shapes. The retrieval function is then defined as a Flexible Multicriteria fusion Function producing ranked results. The evaluation experiments showed that this system can be suited to different retrieval purposes, and that generally the combination of the distinct shape indexing criteria increases both Recall and Precision with respect to the application of any single indexing criterion alone. Gloria Bordogna, Luca Ghilardi, Simone Milesi, Marco Pagani |
SIGIR | 2 |