Channel–Spatial Segmentation Network for Classifying Leaf Diseases
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Lin, Yu & Lu, Qin & Tan, Bin & Yu, Yuanyuan, 2022. "Forecasting energy prices using a novel hybrid model with variational mode decomposition," Energy, Elsevier, vol. 246(C).
- Iftikhar Ahmad & Muhammad Hamid & Suhail Yousaf & Syed Tanveer Shah & Muhammad Ovais Ahmad, 2020. "Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection," Complexity, Hindawi, vol. 2020, pages 1-6, September.
- Ozguven, Mehmet Metin & Adem, Kemal, 2019. "Automatic detection and classification of leaf spot disease in sugar beet using deep learning algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
- Umesh Kumar Lilhore & Agbotiname Lucky Imoize & Cheng-Chi Lee & Sarita Simaiya & Subhendu Kumar Pani & Nitin Goyal & Arun Kumar & Chun-Ta Li, 2022. "Enhanced Convolutional Neural Network Model for Cassava Leaf Disease Identification and Classification," Mathematics, MDPI, vol. 10(4), pages 1-19, February.
- Gary Storey & Qinggang Meng & Baihua Li, 2022. "Leaf Disease Segmentation and Detection in Apple Orchards for Precise Smart Spraying in Sustainable Agriculture," Sustainability, MDPI, vol. 14(3), pages 1-14, January.
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.- Junhao Wu & Yuan Hu & Daqing Wu & Zhengyong Yang, 2022. "An Aquatic Product Price Forecast Model Using VMD-IBES-LSTM Hybrid Approach," Agriculture, MDPI, vol. 12(8), pages 1-26, August.
- Maurizio Bressan & Elena Campagnoli & Carlo Giovanni Ferro & Valter Giaretto, 2022. "Rice Straw: A Waste with a Remarkable Green Energy Potential," Energies, MDPI, vol. 15(4), pages 1-15, February.
- Normaisharah Mamat & Mohd Fauzi Othman & Rawad Abdoulghafor & Samir Brahim Belhaouari & Normahira Mamat & Shamsul Faisal Mohd Hussein, 2022. "Advanced Technology in Agriculture Industry by Implementing Image Annotation Technique and Deep Learning Approach: A Review," Agriculture, MDPI, vol. 12(7), pages 1-35, July.
- Beibei Hu & Yunhe Cheng, 2023. "Prediction of Regional Carbon Price in China Based on Secondary Decomposition and Nonlinear Error Correction," Energies, MDPI, vol. 16(11), pages 1-22, May.
- Haider A. Khan & Shahryar Ghorbani & Elham Shabani & Shahab S. Band, 2024. "Enhancement of Neural Networks Model’s Predictions of Currencies Exchange Rates by Phase Space Reconstruction and Harris Hawks’ Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 835-860, February.
- Rodica Gabriela Dawod & Ciprian Dobre, 2022. "Automatic Segmentation and Classification System for Foliar Diseases in Sunflower," Sustainability, MDPI, vol. 14(18), pages 1-16, September.
- Yunlong Ding & Di-Rong Chen, 2023. "Optimization Based Layer-Wise Pruning Threshold Method for Accelerating Convolutional Neural Networks," Mathematics, MDPI, vol. 11(15), pages 1-13, July.
- Vinay Gautam & Naresh K. Trivedi & Aman Singh & Heba G. Mohamed & Irene Delgado Noya & Preet Kaur & Nitin Goyal, 2022. "A Transfer Learning-Based Artificial Intelligence Model for Leaf Disease Assessment," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
- Jesús Molina‐Muñoz & Andrés Mora‐Valencia & Javier Perote, 2024. "Predicting carbon and oil price returns using hybrid models based on machine and deep learning," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
- Guici Chen & Tingting Zhang & Wenyu Qu & Wenbo Wang, 2023. "Photovoltaic Power Prediction Based on VMD-BRNN-TSP," Mathematics, MDPI, vol. 11(4), pages 1-14, February.
- Alexandru Matei & Stefan-Alexandru Precup & Dragos Circa & Arpad Gellert & Constantin-Bala Zamfirescu, 2023. "Estimating Travel Time for Autonomous Mobile Robots through Long Short-Term Memory," Mathematics, MDPI, vol. 11(7), pages 1-19, April.
- Wang, Jia & Wang, Xinyi & Wang, Xu, 2024. "International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
- Guan, Keqin & Gong, Xu, 2023. "A new hybrid deep learning model for monthly oil prices forecasting," Energy Economics, Elsevier, vol. 128(C).
- Ma, Yilin & Wang, Yudong & Wang, Weizhong & Zhang, Chong, 2023. "Portfolios with return and volatility prediction for the energy stock market," Energy, Elsevier, vol. 270(C).
- Bulent Tugrul & Elhoucine Elfatimi & Recep Eryigit, 2022. "Convolutional Neural Networks in Detection of Plant Leaf Diseases: A Review," Agriculture, MDPI, vol. 12(8), pages 1-21, August.
- Iwona Jaskulska & Jarosław Kamieniarz & Dariusz Jaskulski & Maja Radziemska & Martin Brtnický, 2023. "Fungicidal Protection as Part of the Integrated Cultivation of Sugar Beet: An Assessment of the Influence on Root Yield in a Long-Term Study," Agriculture, MDPI, vol. 13(7), pages 1-10, July.
More about this item
Keywords
plant disease; channel attention; spatial attention; evaluation metrics; CBAM; disease degree;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:12:y:2022:i:11:p:1886-:d:968132. 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.