ICANN 2021 : International Conference on Artificial Neural Networks (ICANN)

The ranking presented on this page offers a comprehensive evaluation of scientific conferences within the field of Engineering and Technology. Developed by Research.com—one of the leading platforms providing trusted data and analytics on scientific contributions since 2014—this ranking is a reliable resource for scholars, institutions, and professionals seeking evidence-based insights into the impact and reputation of conferences.

Each conference's position within the ranking is determined by Research.com's unique bibliometric score, which is meticulously computed using both the estimated h-index and the presence of leading scientists who have presented at the conference over the past three years. This dual-criteria approach enables a robust assessment that captures both citation influence and prominence within the global scientific community.

The ranking is based on Impact Score values gathered as of 2024-11-27, reflecting the most current and comprehensive data available. The evaluation process involved the examination of more than 2,262 conferences, rigorously selected following detailed inspection and critical analysis of over 26,934 scientific documents published within the most recent three-year period. These works were authored or co-authored by 9,385 distinguished and widely respected scientists acknowledged for their ongoing contributions to the field of Engineering and Technology.

To ensure transparency and enable deeper understanding of the methodology underlying the ranking, more details regarding the calculation of the bibliometric score and conference selection process are fully documented on our Methodology Page.

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.

Top authors and change over time

The top authors publishing at International Conference on Artificial Neural Networks (based on the number of publications) are:

• Stefan Wermter (28 papers) published 5 papers at the last edition, 1 more than at the previous edition,
• Alessandro E. P. Villa (19 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• Cornelius Weber (14 papers) published 2 papers at the last edition the same number as at the previous edition,
• Timo Honkela (13 papers) absent at the last edition,
• Martin Bogdan (12 papers) published 1 paper at the last edition the same number as 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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at International Conference on Artificial Neural Networks (based on the number of publications) are:

• University of Málaga (48 papers) absent at the last edition,
• Aalto University (38 papers) absent at the last edition,
• University of Granada (32 papers) absent at the last edition,
• University of Hamburg (27 papers) published 6 papers at the last edition, 3 more than at the previous edition,
• Autonomous University of Madrid (27 papers) published 9 papers at the last edition, 8 more 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 2018 edition, 5.99% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 10.78% were posted by at least one author from the top 10 institutions publishing at the conference. Another 4.41% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.67% of all publications and 68.14% 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.