Article Processing Charges Waived Until 2022
The Science Partner Journal Plant Phenomics is pleased to announce a special issue on Image Analysis and Machine Learning for Cyber-Agricultural Systems .
Today, efficient and cost-effective sensors, as well as high-performance computing technologies, are looking to transform traditional plant-based agriculture into an efficient cyber-physical system. The easy availability of cheap, deployable, connected sensor technology has created an enormous opportunity to collect a vast amount of data at varying spatial and temporal scales at both experimental and production agriculture levels. Therefore, both offline and real-time agricultural analytics that assimilate such heterogeneous data and provide automated, actionable information is critically needed for sustainable and profitable agriculture. The application of advanced image processing and machine learning methods to this critical societal need can be viewed as a transformative extension for the agriculture community. We are looking for papers that present image analysis and machine learning algorithms, experimental technologies, software, pipelines, and new results for Cyber-Agricultural applications for the special issue on “Image analysis and Machine Learning for Cyber-Agricultural Systems.”
Plant Phenomics is an international open access journal published in affiliation with Nanjing Agricultural University (NAU) and distributed by the American Association for the Advancement of Science (AAAS). The journal publishes novel research that can advance all aspects of plant phenotyping in whole plant or cellular levels through novel mathematical and computational technologies in phenotypic data analyses.
Interested in submitting your research for consideration for publication in Plant Phenomics? Learn more about Plant Phenomics and how to submit your manuscript here.
All Article Processing Charges (APCs) are waived through December 31, 2021.
The deadline for submission is March 1, 2020. Please use the “Special Issue” article type when submitting and specify "MLCAS 2019” in your cover letter if you have presented your paper in MLCAS 2019.
We hope that you will consider submitting your research to Plant Phenomics.
Seishi Ninomiya, PhD, University of Tokyo
Frédéric Baret, PhD, French National Institute of Agricultural Research
Zong-Ming Cheng, PhD, Nanjing Agricultural University/University of Tennessee
For further inquiries, please contact guest editors:
Wei Guo, University of Tokyo at firstname.lastname@example.org
Soumik Sarkar, Iowa State University at email@example.com
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