EDBT 2026 Demo / reviewers in the wild / expert
Ikuji Honda
dblp:81/9703
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1983
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 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.
| Artificial intelligence
1 paper |
Image recognition and object detection · 100% | |
| Computer graphics and multimedia
1 paper |
Geometric modeling and processing · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Image recognition and object detection › object recognition
curved object recognition |
0.0 | 1 | 1983 | Pseudodistance Measures for Recognition of Curved Objects · IEEE Trans. Pattern Anal. Mach. Intell. 1983 |
Computer vision › Image recognition and object detection
object recognition |
0.0 | 1 | 1983 | Pseudodistance Measures for Recognition of Curved Objects · IEEE Trans. Pattern Anal. Mach. Intell. 1983 |
Geometric modeling and processing › shape descriptor
fourier descriptors |
0.0 | 1 | 1983 | Pseudodistance Measures for Recognition of Curved Objects · IEEE Trans. Pattern Anal. Mach. Intell. 1983 |
Geometric modeling and processing
shape description |
0.0 | 1 | 1983 | Pseudodistance Measures for Recognition of Curved Objects · IEEE Trans. Pattern Anal. Mach. Intell. 1983 |
Methods — techniques the papers use, named apart from their topics
pseudodistance measures · 0.0fourier series expansion · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1983 | Pseudodistance Measures for Recognition of Curved ObjectsabstractA method for the description and identification of curved objects is described in this paper. The shape of a curved object is considered as a surface which is an accumulation of horizontal section boundaries. This is described by the coefficients of a Fourier series expansion of the proposed representative function. Each complicated feature of the shape of the object is decomposed into five simple features: elongatedness, horizontal strain, section shape, torsion, and displacement. Differences of objects as patterns are defined as pseudodistances of corresponding features. Some essential properties such as completeness of the pseudodistance family are explained theoretically. Finally, experimental results of identification of wooden block models and a doll are displayed. Yukio Sato, Ikuji Honda |
IEEE Trans. Pattern Anal. Mach. Intell. | 2 |