Wheat Spike Blast Image Classification Using Deep Convolutional Neural Networks.

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Bibliographic Details
Title: Wheat Spike Blast Image Classification Using Deep Convolutional Neural Networks.
Authors: Fernández-Campos M; Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, United States., Huang YT; Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, United States., Jahanshahi MR; Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, United States.; School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States., Wang T; Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, United States., Jin J; Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, United States., Telenko DEP; Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, United States., Góngora-Canul C; Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, United States.; Tecnológico Nacional de México/IT Conkal, Conkal, Yucatán, Mexico., Cruz CD; Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, United States.
Source: Frontiers in plant science [Front Plant Sci] 2021 Jun 17; Vol. 12, pp. 673505. Date of Electronic Publication: 2021 Jun 17 (Print Publication: 2021).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101568200 Publication Model: eCollection Cited Medium: Print ISSN: 1664-462X (Print) Linking ISSN: 1664462X NLM ISO Abbreviation: Front Plant Sci Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1664-462X
DOI:10.3389/fpls.2021.673505