EDBT 2026 Demo / reviewers in the wild / expert
Pedro Paulo Cortopassi
dblp:201/1701
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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.
| Artificial intelligence
1 paper |
Image recognition and object detection · 67% Segmentation and scene understanding · 33% | |
| Computer graphics and multimedia
1 paper |
Geometric modeling and processing · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Image recognition and object detection
object recognition |
0.0 | 1 | 1988 | Using perceptual grouping to recognize and locate partially occluded objects · CVPR 1988 |
Computer vision › Image recognition and object detection › object recognition › robust object recognition
occluded object recognition |
0.0 | 1 | 1988 | Using perceptual grouping to recognize and locate partially occluded objects · CVPR 1988 |
Computer vision › Segmentation and scene understanding
perceptual grouping |
0.0 | 1 | 1988 | Using perceptual grouping to recognize and locate partially occluded objects · CVPR 1988 |
Geometric modeling and processing › shape decomposition
convex decomposition |
0.0 | 1 | 1988 | A computationally efficient algorithm for shape decomposition · CVPR 1988 |
Geometric modeling and processing
shape decomposition |
0.0 | 1 | 1988 | A computationally efficient algorithm for shape decomposition · CVPR 1988 |
Geometric modeling and processing
shape representation |
0.0 | 1 | 1988 | A computationally efficient algorithm for shape decomposition · CVPR 1988 |
Methods — techniques the papers use, named apart from their topics
eidetic representation · 0.0convex decomposition · 0.0constraint propagation · 0.0connectionist network · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | A computationally efficient algorithm for shape decompositionabstractAn algorithm is described that is capable of decomposing homogeneous image regions into a complete set of convex parts ordered by size. The process is information-preserving and computationally efficient, and does not require prior edge smoothing. Shape decomposition is useful for parsing undersegmented image regions into which parts correspond to separate semantic entities. The algorithm is efficient because it operates on a list-oriented form of shape representation. Results of decomposing several different shapes are presented and discussed.> Pedro Paulo Cortopassi, T. C. Rearick |
CVPR | 1 |
| 1988 | Using perceptual grouping to recognize and locate partially occluded objectsabstractThe authors describe a connectionist network which is not a neural net in which knowledge is distributed globally via the connections of functionally simple nodes. The technique combines constraint propagation with analogical or eidetic representations. It represents an alternative to the atomistic signals-to-symbols paradigm in which a one-to-one correspondence is assumed to exist between symbols and the concepts they represent.> T. C. Rearick, J. L. Frawley, Pedro Paulo Cortopassi |
CVPR | 3 |
| 1987 | Expert Systems for thermal and Structural Analysis in Electronic System DesignabstractThis paper presents an application of rule-based expert systems to thermal and structural analysis, part of mechanical engineering design, in electronic system design. The purpose of these expert systems is to serve as a consultant or design reviewer. These design expert systems are capable of performing both symbolic reasoning and numeric computation. The advantages of expert systems over conventional systems such as user friendliness, explanation and help facilities, and easy development and maintenance are also shown in this paper. Using system-subsystem tree structure several interrelated expert systems can be integrated into one system, and it is flexible for future expansion or modification. Object-oriented approach is also discussed, which with its unique representation of object could be a useful tool for engineering design. Hsi-Ho Liu, Ying-Nan Lai, Pedro Paulo Cortopassi |
Int. J. Pattern Recognit. Artif. Intell. | 3 |