Abstract
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Yibin Wang, Al Bashir, Partho Ghose, Mike Ojo, Azlan Zahid
Abstract
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crossref
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Peduncle detection of sweet pepper for autonomous crop harvesting—combined color and 3-D information
10.1109/lra.2017.2651952 · doi-reference
Application of an image and environmental sensor network for automated greenhouse insect pest monitoring
10.1016/j.aspen.2019.11.006 · doi-reference
A system for the monitoring and predicting of data in precision agriculture in a rose greenhouse based on wireless sensor networks
10.1016/j.procs.2017.11.042 · doi-reference
RGB cams vs RGB-D sensors: low cost motion capture technologies performances and limitations
10.1016/j.jmsy.2014.07.011 · doi-reference
10.2139/ssrn.5142250
10.2139/ssrn.5142250 · doi-reference
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10.1109/access.2022.3152544 · doi-reference
Digital Twins in agriculture: challenges and opportunities for environmental sustainability
10.1016/j.cosust.2022.101252 · doi-reference
Neural network model for greenhouse microclimate predictions
10.3390/agriculture12060780 · doi-reference
Deep learning in controlled environment agriculture: a review of recent advancements, challenges and prospects
10.3390/s22207965 · doi-reference
Incorporating artificial intelligence technology in smart greenhouses: current State of the Art
10.3390/app13010014 · doi-reference
Systematic approach to validate and implement digital phenotyping tool for soybean: a case study with PlantEye
10.1002/ppj2.20025 · doi-reference
Greenhouse environment modeling and simulation for microclimate control
10.1016/j.compag.2019.04.013 · doi-reference
Direct and indirect measurements of LAI in millet and fallow vegetation in HAPEX-Sahel
10.1016/s0168-1923(98)00092-6 · doi-reference
An artificial intelligence-powered environmental control system for resilient and efficient greenhouse farming
10.3390/su162410958 · doi-reference
Comparison of land, water, and energy requirements of lettuce grown using hydroponic vs. conventional agricultural methods
10.3390/ijerph120606879 · doi-reference
Vulnerability of specialty crops to short-term climatic variability and adaptation strategies in the Midwestern USA
10.1007/s10584-017-2066-1 · doi-reference
Vulnerability of California specialty crops to projected mid-century temperature changes
10.1007/s10584-017-2011-3 · doi-reference
Energy optimization and plant comfort management in smart greenhouses using the artificial bee colony algorithm
10.1038/s41598-024-84141-5 · doi-reference
Exploiting pre-trained convolutional neural networks for the detection of nutrient deficiencies in hydroponic basil
10.3390/s23125407 · doi-reference
Evaluation of end effectors for robotic harvesting of mango fruit
10.3390/su15086769 · doi-reference
A meta-analysis: food production and vegetable crop yields of hydroponics
10.1016/j.scienta.2023.112339 · doi-reference
Decision support systems and models for aiding irrigation and nutrient management of vegetable crops
10.1016/j.agwat.2020.106209 · doi-reference
NeRF-based 3D reconstruction pipeline for acquisition and analysis of tomato crop morphology
10.3389/fpls.2024.1439086 · doi-reference
Integrating reinforcement learning and large language models for crop production process management optimization and control through a new knowledge-based deep learning paradigm
10.1016/j.compag.2025.110028 · doi-reference
Agricultural robotics: unmanned robotic service units in agricultural tasks
10.1109/mie.2013.2252957 · doi-reference
Integrating neural network for pest detection in controlled environment vertical farm
10.17485/ijst/v15i17.353 · doi-reference
Smart control models used for nutrient management in hydroponic crops: a systematic review
10.1109/access.2025.3526171 · doi-reference
Albumentations: fast and flexible image augmentations
10.3390/info11020125 · doi-reference
10.32473/edis-fe1041-2018
10.32473/edis-fe1041-2018 · doi-reference
A field‐tested robotic harvesting system for iceberg lettuce
10.1002/rob.21888 · doi-reference
Development of an end-effector for robotic harvesting of hydroponic lettuce
10.13031/ja.16269 · doi-reference