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IEEE

ICDAR 2021 : International Conference on Document Analysis and Recognition (ICDAR)

Location: Lausanne , Switzerland

Submission deadline: 2/8/2021

Conference dates: 9/5/2021 - 9/5/2021

Research H-index
6

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 589 24 14 6

Call for Papers

Topics of Interest
----------------------------
Document image processing
Physical and logical layout analysis
Text and symbol recognition
Handwriting recognition
Document analysis systems
Document classification
Indexing and retrieval of documents
Document synthesis
Extracting document semantics
NLP for document understanding
Document summarization and translation
Office automation
Human document interaction

Multimedia document analysis
Mobile text recognition
Pen‐based document analysis
Scene text detection and recognition
Graphics recognition
Recognition of tables and formulas
Historical document analysis
Signature verification
Document forensics and provenance analysis
Medical document analysis
Document analysis for social good
Document analysis for literature search
Gold-standard benchmarks and data sets

Overview

The scientific conference ranking presented on this page provides a comprehensive evaluation of leading events in the field of Computer Science. The ranking has been meticulously prepared by Research.com, a respected authority in scientific research and analytics across all major disciplines. Since 2014, Research.com has been recognized for delivering trusted data on scientific contributions and excellence, with a particular emphasis on objectivity and rigor.

Conference positions in this ranking are determined using Research.com's proprietary bibliometric score. This unique metric is carefully computed based on the estimated h-index and the number of leading scientists who have participated in each conference during the past three years. This dual approach more accurately reflects both the impact and the influence of each event within the research community.

The ranking includes Impact Score values as of 2024-11-27, ensuring that the assessment reflects the most current data available. The process of compiling this ranking was extensive and thorough: more than 2,742 conferences were evaluated, each selected following a detailed inspection and a rigorous analysis of over 148,739 scientific documents published across the most recent three years. Contributions from 13,184 leading and well-respected scientists in Computer Science were considered, highlighting the depth and breadth of the analysis undertaken.

For readers interested in further understanding the intricacies of how these ranking scores are computed, a comprehensive explanation of the methodology is available on our Methodology Page. This transparency underscores our commitment to academic integrity and to providing the scientific community with reliable, actionable insights.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing at International Conference on Document Analysis and Recognition (based on the number of publications) are:

  • Umapada Pal (47 papers) published 5 papers at the last edition, 3 less than at the previous edition,
  • Jean-Marc Ogier (47 papers) published 8 papers at the last edition, 2 less than at the previous edition,
  • Cheng-Lin Liu (45 papers) published 8 papers at the last edition the same number as at the previous edition,
  • Seiichi Uchida (43 papers) published 12 papers at the last edition, 7 more than at the previous edition,
  • Andreas Dengel (38 papers) published 10 papers at the last edition, 1 less than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing at International Conference on Document Analysis and Recognition (based on the number of publications) are:

  • Indian Statistical Institute (59 papers) published 8 papers at the last edition, 9 less than at the previous edition,
  • University of La Rochelle (57 papers) published 10 papers at the last edition, 1 less than at the previous edition,
  • Autonomous University of Barcelona (52 papers) published 9 papers at the last edition, 11 less than at the previous edition,
  • Kaiserslautern University of Technology (47 papers) published 5 papers at the last edition, 13 less than at the previous edition,
  • Chinese Academy of Sciences (45 papers) published 14 papers at the last edition, 2 less than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2019 edition, 6.65% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 24.92% were posted by at least one author from the top 10 institutions publishing at the conference. Another 9.06% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.86% of all publications and 50.16% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

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