1. Annotated Plant Pathology Databases for Image-Based Detection and Recognition of Diseases
- Author
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Kátia de Lima Nechet, Luciano Vieira Koenigkan, Daniel Terao, Flavia Rodrigues Alves Patricio, Rodrigo Veras Costa, Fábio Rossi Cavalcanti, Saulo Alves Santos de Oliveira, José Maurício Cunha Fernandes, Jayme Garcia Arnal Barbedo, Claudia Vieira Godoy, T. T. Santos, Viviane Talamini, A. K. N. Ishida, Murillo Lobo Junior, Luiz Gonzaga Chitarra, Bernardo de Almeida Halfeld-Vieira, and Francislene Angelotti
- Subjects
0106 biological sciences ,General Computer Science ,Database ,Computer science ,business.industry ,Deep learning ,Image processing ,02 engineering and technology ,computer.software_genre ,01 natural sciences ,Plant disease ,0202 electrical engineering, electronic engineering, information engineering ,Plant species ,020201 artificial intelligence & image processing ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,computer ,Image based ,010606 plant biology & botany - Abstract
Over the last few years, considerable effort has been spent by Embrapa in the construction of a plant disease database representative enough for the development of effective methods for automatic plant disease detection and recognition. In October of 2016, this database, called PDDB, had 2326 images of 171 diseases and other disorders affecting 21 plant species. PDDB size, although considerable, is not enough to allow the use of powerful techniques such as deep learning. In order to increase its size, each image was subdivided according to certain criteria, increasing the number of images to 46,513. Both the original (PDDB) and subdivided (XDB) databases are now being made freely available for academic research purposes, thus supporting new studies and contributing to speed up the advances in the area. Both collections are expected to grow continuously in order to expand their reach. PDDB and XDB can be accessed in the link https://www.digipathos-rep.cnptia.embrapa.br/.
- Published
- 2018
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