Demo Data from SIGIR 2026 / reviewers in the wild / expert
Kiyomichi Kurino
dblp:324/9141
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1992
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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.
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% | |
| Artificial intelligence
1 paper |
Image recognition and object detection · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › document image analysis
character segmentation |
0.0 | 1 | 1992 | Segmentation methods for character recognition: from segmentation to document structure analysis · Proc. IEEE 1992 |
Image and video processing
document image analysis |
0.0 | 1 | 1992 | Segmentation methods for character recognition: from segmentation to document structure analysis · Proc. IEEE 1992 |
Computer vision › Image recognition and object detection › text recognition
optical character recognition |
0.0 | 1 | 1992 | Segmentation methods for character recognition: from segmentation to document structure analysis · Proc. IEEE 1992 |
Methods — techniques the papers use, named apart from their topics
pattern-oriented segmentation · 0.0multiple hypothesis verification · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1992 | Segmentation methods for character recognition: from segmentation to document structure analysisabstractA pattern-oriented segmentation method for optical character recognition that leads to document structure analysis is presented. As a first example, segmentation of handwritten numerals that touch are treated. Connected pattern components are extracted, and spatial interrelations between components are measured and grouped into meaningful character patterns. Stroke shapes are analyzed and a method of finding the touching positions that separates about 95% of connected numerals correctly is described. Ambiguities are handled by multiple hypotheses and verification by recognition. An extended form of pattern-oriented segmentation, tabular form recognition, is considered. Images of tabular forms are analyzed, and frames in the tabular structure are extracted. By identifying semantic relationships between label frames and data frames, information on the form can be properly recognized.> Hiromichi Fujisawa, Yasuaki Nakano, Kiyomichi Kurino |
Proc. IEEE | 3 |