Wheat ear counting using K-means clustering segmentation and convolutional neural network
Sign Up to like & getrecommendations! Published in 2020 at "Plant Methods"
DOI: 10.1186/s13007-020-00648-8
Abstract: Background Wheat yield is influenced by the number of ears per unit area, and manual counting has traditionally been used to estimate wheat yield. To realize rapid and accurate wheat ear counting, K-means clustering was… read more here.
Keywords: ear counting; wheat; means clustering; wheat ear ... See more keywords
DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2019 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2019.01176
Abstract: Crop yield is an essential measure for breeders, researchers, and farmers and is composed of and may be calculated by the number of ears per square meter, grains per ear, and thousand grain weight. Manual… read more here.
Keywords: ear counting; using simple; wheat; field ... See more keywords