Estimation of Greenhouse Lettuce Growth Indices Based on a Two-Stage CNN Using RGB-D Images

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 15; p. 5499
• Main Authors: Gang, Min-Seok, Kim, Hak-Jin, Kim, Dong-Wook
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.07.2022; MDPI
• Subjects: Cameras; convolutional neural network (CNN); Crops; Datasets; Deep learning; greenhouse; Greenhouses; growth estimation; growth index; growth monitoring; Humans; Lactuca - classification; Lactuca - growth & development; Lettuce; Neural networks; Neural Networks, Computer; Performance evaluation; Plant Leaves - growth & development; Plant Roots - growth & development; Processing speed; Regression analysis; United States > US; growth estimation; stereo camera; convolutional neural network (CNN); growth index; greenhouse; lettuce; red, green, blue, and depth (RGB-D); growth monitoring

Growth indices can quantify crop productivity and establish optimal environmental, nutritional, and irrigation control strategies. A convolutional neural network (CNN)-based model is presented for estimating various growth indices (i.e., fresh weight, dry weight, height, leaf area, and diameter) of...