Special Issue "Applications of Machine Learning and Deep Learning in Agriculture"
Deadline for manuscript submissions: 30 September 2022 | Viewed by 2100
Interests: mining software repositories; recommender systems; semantic web and linked data; machine learning/deep learning with applications in healthcare and agriculture
Deep learning algorithms enable machines to simulate humans’ learning activities and acquire real-world knowledge by generalizing from data. In this way, they are capable of identifying patterns and making decisions solely by means of data, without resorting to constant interventions from humans. The combination of deep neural networks with transfer learning is a successful strategy to address the problem of training a model given a limited amount of data. In this respect, deep learning has gained momentum, and its applications can be seen in a wide range of domains. To date, various fuzzy inference and computational intelligence techniques have been deployed to empower agricultural systems. Among others, the deployment of digital technologies to facilitate farming activities has been on the rise in recent years.
Our Special Issue titled “Applications of Machine Learning and Deep Learning in Agriculture” offers a venue for researchers and practitioners to share their experience on the evaluation and in-depth investigation of machine learning/deep learning and their applications in real life, with focus on the agriculture sector. We solicit research work to increase synergy among various communities, including machine learning, agricultural informatics, and recommender systems.
Topics of interest for the Special Issue include but are not limited to:
- Applications of machine learning and deep learning techniques in agricultural systems;
- Deep learning for recommender systems;
- Deep learning for building expert systems in agriculture to support harvest and production;
- Case studies of real-world implementations for expert systems;
- Adversarial machine learning in agricultural systems: risks and countermeasures;
- Reinforcement learning and applications in agricultural imaging;
- Transfer learning;
- Recommender systems for supporting smart farming.
Dr. Phuong T. Nguyen
Dr. Vito Walter Anelli
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Informatics is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- deep learning
- transfer learning
- agrucultural systems
- expert systems
- recommender systems