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Improved sap flow prediction: A comparative deep learning study based on LSTM, BiLSTM, LRCN, and GRU with stem diameter data

Introduction Recording sap flow in plants is essential to understanding water usage, especially for herbaceous species like tomatoes. While plant physiology research has progressed, there remains a gap in applying sap flow sensor data to these species. In this study, the predictive...

Improved sap flow prediction: A comparative deep learning study based on LSTM, BiLSTM, LRCN, and GRU with stem diameter data

An advanced approach to tomato apex head thickness measurement using lightweight YOLO variants, faster RCNN, and RGB-depth sensor

This study presents an automated method for detecting and measuring the apex head thickness of tomato plants, a critical phenotypic trait associated with plant health, fruit development, and yield forecasting. Due to the apex's sensitivity to physical contact, non-invasive monitoring...

An advanced approach to tomato apex head thickness measurement using lightweight YOLO variants, faster RCNN, and RGB-depth sensor
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