Lettuce Plant Trace-Element-Deficiency Symptom Identification via Machine Vision Methods
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Zhao, Yang & Li, Jianping & Yu, Lean, 2017. "A deep learning ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 66(C), pages 9-16.
- Jinzhu Lu & Lijuan Tan & Huanyu Jiang, 2021. "Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification," Agriculture, MDPI, vol. 11(8), pages 1-18, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Jen-Yu Lee & Tien-Thinh Nguyen & Hong-Giang Nguyen & Jen-Yao Lee, 2022. "Towards Predictive Crude Oil Purchase: A Case Study in the USA and Europe," Energies, MDPI, vol. 15(11), pages 1-15, May.
- Shao, Zhen & Zheng, Qingru & Yang, Shanlin & Gao, Fei & Cheng, Manli & Zhang, Qiang & Liu, Chen, 2020. "Modeling and forecasting the electricity clearing price: A novel BELM based pattern classification framework and a comparative analytic study on multi-layer BELM and LSTM," Energy Economics, Elsevier, vol. 86(C).
- Apostolos Ampountolas & Titus Nyarko Nde & Paresh Date & Corina Constantinescu, 2021. "A Machine Learning Approach for Micro-Credit Scoring," Risks, MDPI, vol. 9(3), pages 1-20, March.
- Zhang, Hong & Nguyen, Hoang & Bui, Xuan-Nam & Pradhan, Biswajeet & Mai, Ngoc-Luan & Vu, Diep-Anh, 2021. "Proposing two novel hybrid intelligence models for forecasting copper price based on extreme learning machine and meta-heuristic algorithms," Resources Policy, Elsevier, vol. 73(C).
- Radosław Puka & Bartosz Łamasz & Marek Michalski, 2021. "Effectiveness of Artificial Neural Networks in Hedging against WTI Crude Oil Price Risk," Energies, MDPI, vol. 14(11), pages 1-26, June.
- Xia Hao & Man Zhang & Tianru Zhou & Xuchao Guo & Federico Tomasetto & Yuxin Tong & Minjuan Wang, 2021. "An Automatic Light Stress Grading Architecture Based on Feature Optimization and Convolutional Neural Network," Agriculture, MDPI, vol. 11(11), pages 1-17, November.
- Mst. Shapna Akter & Hossain Shahriar & Reaz Chowdhury & M. R. C. Mahdy, 2022. "Forecasting the Risk Factor of Frontier Markets: A Novel Stacking Ensemble of Neural Network Approach," Future Internet, MDPI, vol. 14(9), pages 1-23, August.
- Feng, Qianqian & Sun, Xiaolei & Hao, Jun & Li, Jianping, 2021. "Predictability dynamics of multifactor-influenced installed capacity: A perspective of country clustering," Energy, Elsevier, vol. 214(C).
- Mingfeng Huang & Guoqin Xu & Junyu Li & Jianping Huang, 2021. "A Method for Segmenting Disease Lesions of Maize Leaves in Real Time Using Attention YOLACT++," Agriculture, MDPI, vol. 11(12), pages 1-14, December.
- Liwen Ling & Dabin Zhang & Shanying Chen & Amin W. Mugera, 2020. "Can online search data improve the forecast accuracy of pork price in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 671-686, July.
- Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020.
"Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary,"
Papers
2009.07341, arXiv.org.
- Dimitriadis, Timo & Liu, Xiaochun & Schnaitmann, Julie, 2020. "Encompassing tests for value at risk and expected shortfall multi-step forecasts based on inference on the boundary," Hohenheim Discussion Papers in Business, Economics and Social Sciences 11-2020, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
- Lin, Ling & Jiang, Yong & Xiao, Helu & Zhou, Zhongbao, 2020. "Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).
- Zhang, Shuai & Chen, Yong & Xiao, Jiuhong & Zhang, Wenyu & Feng, Ruijun, 2021. "Hybrid wind speed forecasting model based on multivariate data secondary decomposition approach and deep learning algorithm with attention mechanism," Renewable Energy, Elsevier, vol. 174(C), pages 688-704.
- Ke Yan & Yuting Dai & Meiling Xu & Yuchang Mo, 2019. "Tunnel Surface Settlement Forecasting with Ensemble Learning," Sustainability, MDPI, vol. 12(1), pages 1-11, December.
- Qi Zhang & Yi Hu & Jianbin Jiao & Shouyang Wang, 2022. "Exploring the Trend of Commodity Prices: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
- Brown, Bijon & Schoney, Richard & Nolan, James, 2021. "Assessing the food vs. fuel issue: An agent-based simulation," Energy Policy, Elsevier, vol. 159(C).
- Fahman Saeed & Muhammad Hussain & Hatim A. Aboalsamh, 2022. "Automatic Fingerprint Classification Using Deep Learning Technology (DeepFKTNet)," Mathematics, MDPI, vol. 10(8), pages 1-17, April.
- Hieu T. T. L. Pham & Mahdi Rafieizonooz & SangUk Han & Dong-Eun Lee, 2021. "Current Status and Future Directions of Deep Learning Applications for Safety Management in Construction," Sustainability, MDPI, vol. 13(24), pages 1-37, December.
- Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2021. "Predicting corporate carbon footprints for climate finance risk analyses: A machine learning approach," Energy Economics, Elsevier, vol. 95(C).
- Zhang, Shuangyi & Li, Xichen, 2021. "Future projections of offshore wind energy resources in China using CMIP6 simulations and a deep learning-based downscaling method," Energy, Elsevier, vol. 217(C).
More about this item
Keywords
deep learning; feature extraction; horticulture; lettuce; machine vision; trace-element deficiency;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:8:p:1614-:d:1217899. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.