{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T08:51:33Z","timestamp":1772614293957,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,11]],"date-time":"2020-07-11T00:00:00Z","timestamp":1594425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Chinese High Technology Research and Development Research Fund","award":["2016YFD0300600 -2016YFD0300606, 2016YFD0300600-2016YFD0300610"],"award-info":[{"award-number":["2016YFD0300600 -2016YFD0300606, 2016YFD0300600-2016YFD0300610"]}]},{"name":"the National Natural Science Fund","award":["31971785, 31501219"],"award-info":[{"award-number":["31971785, 31501219"]}]},{"name":"the Fundamental Research Funds for the Central Universities","award":["2020TC036"],"award-info":[{"award-number":["2020TC036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Maize plant detection was conducted in this study with the goals of target fertilization and reduction of fertilization waste in weed spots and gaps between maize plants. The methods used included two types of color featuring and deep learning (DL). The four color indices used were excess green (ExG), excess red (ExR), ExG minus ExR, and the hue value from the HSV (hue, saturation, and value) color space, while the DL methods used were YOLOv3 and YOLOv3_tiny. For practical application, this study focused on performance comparison in detection accuracy, robustness to complex field conditions, and detection speed. Detection accuracy was evaluated by the resulting images, which were divided into three categories: true positive, false positive, and false negative. The robustness evaluation was performed by comparing the average intersection over union of each detection method across different sub\u2013datasets\u2014namely original subset, blur processing subset, increased brightness subset, and reduced brightness subset. The detection speed was evaluated by the indicator of frames per second. Results demonstrated that the DL methods outperformed the color index\u2013based methods in detection accuracy and robustness to complex conditions, while they were inferior to color feature\u2013based methods in detection speed. This research shows the application potential of deep learning technology in maize plant detection. Future efforts are needed to improve the detection speed for practical applications.<\/jats:p>","DOI":"10.3390\/rs12142229","type":"journal-article","created":{"date-parts":[[2020,7,14]],"date-time":"2020-07-14T09:30:49Z","timestamp":1594719049000},"page":"2229","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Application of Color Featuring and Deep Learning in Maize Plant Detection"],"prefix":"10.3390","volume":"12","author":[{"given":"Haojie","family":"Liu","sequence":"first","affiliation":[{"name":"Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Sun","sequence":"additional","affiliation":[{"name":"Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minzan","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michihisa","family":"Iida","sequence":"additional","affiliation":[{"name":"Graduate School of Agriculture Kyoto University, Kyoto 606-8224, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0065-2113(08)60513-1","article-title":"Aspects of precision agriculture","volume":"67","author":"Pierce","year":"1999","journal-title":"Adv. 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