✔ Conference Proceedings

Submitted paper will be peer reviewed by conference committees, and accepted papers after registration and presentation will be published in the Conference Proceedings, which will be submitted for indexing by Scopus, CNKI, Google Scholar, Inspec (IET).

✔ Journal Recommendation

Call for Papers for the Computers and Electronics in Agriculture

We are pleased to share the Computers and Electronics in Agriculture (ISSN: 0168-1699) with conference attendees. The manuscripts of good quality from this conference will be recommended for submission to its special issue: Generative AI in Smart Agriculture: Advances, Applications and Challenges.

About Computers and Electronics in Agriculture 

Computers and Electronics in Agriculture (ISSN: 0168-1699) is a peer-reviewed hybrid journal that publishes international advances in the development and application of computer hardware, software, electronic instrumentation, and control systems to solve problems in the agricultural sector, including agronomy, horticulture (food and recreational), forestry, aquaculture, and animal husbandry.

•  High Visibility: included in renowned databases such as SCIE, EI ompendex, Scopus, etc.

• Journal Ranking: JCR Q1, CAS Q1

• Rapid Publication: manuscripts are peer reviewed, with an average of 21 days to receive the first decision, 188 days from submission to acceptance, and 10 days after acceptance (data from the journal’s official website)

• Impact Factor: 7.7 (2023-24); 5-year impact factor: 8.2

•  Publishing Model: Hybrid. Authors are required to pay an Article Processing Charge (APC) of 3870 USD if they choose open access publishing. No charges are required if authors choose non-open access publishing

The topics of interest include but are not limited to:

• Multi-modal generated data fusion for deep learning-based agricultural applications

• Crop disease detection and pest management based on deep learning and generated data

• Real-time decision-making systems combined with Generative AI for smart agriculture

• Intelligent irrigation systems using Generative AI and agricultural domain knowledge

• Combination of physical data and generated data in the agricultural digital twin systems

• Security and privacy issues in the use of Generative AI in smart agricultural applications

• Quality evaluation and cleaning of generated data in specific agricultural applications

• Agricultural scene image and video generation, identification, attack and defense

• Distributed collaborative learning based on Generative AI and edge/cloud computing

• Case studies using Generative AI towards efficient smart agricultural applications

ISAEB 2024