I am delighted to inform you that I am one of the guest editors for the Special Issue “Acquire and Perceive: Novel Approaches for Imaging-based Plant Phenotyping” on Remote Sensing (MPDI).
SPECIAL ISSUE INFORMATION
Plants are the fundamental source of food for people, livestock, and all live species on earth. The growth in the human population with 10 billion people expected by 2050, requires an increase of 50% in agriculture production. Crop optimization is approached by multiple means, including automation of agricultural operations and improved plant breeding process, creating an urgent need for plant trait analysis and phenotyping. However, manual plant analysis is tedious, often destructive for the plant, and non-scalable. With improved sensors and recent advances in machine learning (especially deep learning), imaging-based plant analysis provides a promising alternative, with a growing impact.
This Special Issue invites cutting-edge contributions concerning all aspects of the imaging-based plant analysis challenge. Image acquisition is one topic that is of particular interest. Agriculture monitoring is done in complex and changing illumination conditions, often with modalities beyond RGB, such as depth or hyperspectral data. Papers considering illumination condition, illumination design, and joint illumination, as well as acquisition algorithms, sensor fusion, or image processing design, are encouraged. Another topic of interest is image perception—computer vision and machine learning techniques applied to plant analysis from images. Novel phenotyping tasks, as well as methods for improved accuracy, and/or robustness in existing tasks are welcome. Additional topics of interest include (but are not limited to) fine-grained phenotyping, flexibility and task transfer, and phenotype tracking in a time series. Furthermore, people wishing to discuss a topic of particular interest, to outline the next steps and challenges, are welcome to submit review/survey papers.
Dr. Aharon Bar-Hillel
Dr. Mario Valerio Giuffrida
Dr. Iftach Klapp
Contributions can be submitted anytime by the
31 March 2021 31 March 2022 (deadline extended).