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IJCNN 2027

International Joint Conference on Neural Networks

IEEEML
122days left

Paper submission · Jan 31, 2027 est.

On the horizon · deadline is AoE (UTC-12)

All deadlines

Paper submissionJan 31, 2027est.

From past proceedings

Papers in IJCNN's main DBLP volume each year, not official acceptance counts.

Full proceedings stats →

Papers in 2025

2,138

main DBLP volume

5-year change

+91%

vs 2020

Papers, all years

20,286

26 years since 1990

Authors per paper

4.3

3.3 in 2015

By an entirely new team

35%

of 2025 papers

Papers per year1990 to 2025
1990: 429 papers1999: 893 papers2000: 522 papers2003: 589 papers2004: 575 papers2005: 575 papers2006: 787 papers2007: 534 papers2008: 641 papers2009: 520 papers2010: 613 papers2011: 468 papers2012: 490 papers2013: 435 papers2014: 619 papers2015: 559 papers2016: 728 papers2017: 621 papers2018: 754 papers2019: 801 papers2020: 1,122 papers2021: 1,179 papers2022: 1,081 papers2023: 968 papers2024: 1,645 papers2025: 2,138 papers
Read the 2025 proceedingsProceedings ↗DBLP ↗

Top keywords, 2025

detectionnetworkgraphneuralimagefusionattentionclassificationpredictionfeaturesegmentationfederated

Most published at IJCNN

  1. José C. Príncipe1990 to 2025113
  2. Stefan Wermter1999 to 202555
  3. Haibo He2007 to 202552
  4. Teresa Bernarda Ludermir1999 to 202451
  5. Jinglu Hu1999 to 202251

Who publishes here

2025 · papers count once per institution on them

Academia 85%Industry 0%Government and other 15%

Institutions

  1. 1Chinese Academy of Sciences🇨🇳82
  2. 2Xinjiang University🇨🇳44
  3. 3University of Chinese Academy of Sciences🇨🇳43
  4. 4Tsinghua University🇨🇳41
  5. 5Beijing University of Posts and Telecommunications🇨🇳40
  6. 6Sapienza University of Rome🇮🇹39
  7. 7Zhejiang University🇨🇳36
  8. 8Institute of Information Engineering🇨🇳32

Countries

  1. China1382
  2. Italy172
  3. United States159
  4. United Kingdom85
  5. India62
  6. Australia59

Affiliations from OpenAlex for the papers DBLP lists. A paper with authors from three institutions counts for each of them; the split above is over the top institutions.