A Transfer Learning Approach Using Densely Connected Convolutional Network for Maize Leaf Diseases Classification-Reference-Cited by-同舟云学术

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A Transfer Learning Approach Using Densely Connected Convolutional Network for Maize Leaf Diseases Classification

Published:2021 Issue: Volume: Page:369-382
ISSN:2194-5357
Container-title:Computational Vision and Bio-Inspired Computing
language:
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Author:

Baldota Siddhant,Sharma Rubal,Khaitan Nimisha,Poovammal E.

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-33-6862-0_31

Reference14 articles.

1. S. Kumar, B. Raghavendra, Disease detection of various plant leaf using image processing techniques. in International Conference on Advanced Computing and Communication Systems(2019). https://doi.org/10.1109/ICCUBEA.2015.153

2. T. Tan, Z. Li, H. Liu, F. Zanjani, Q. Ouyang, Y. Tang, Z. Hu, Q. Li, Optimize transfer learning for lung diseases in bronchoscopy using new concept: sequential Fine-Tuning. IEEE J. Transitional Eng. Health Med. (2018).https://doi.org/10.1109/JTEHM.2018.2865787

3. K. Panigrahi, H. Das, A. Sahoo, S. Moharana, Maize Leaf detection and classification using machine learning algorithms. Advances in intelligent systems and computing, vol. 1119 (2020).https://doi.org/10.1007/978-981-15-2414-1_66

4. J. Shah, H. Prajapati, V. Dabhi, A survey on detection and classification of rice plant diseases. in IEEE International Conference (2016). https://doi.org/10.1109/ICCTAC.2016.7567333

5. P. Thakur, P. Aggarwal, M. Juneja, Contagious disease detection in cereals crops and classification as solid or undesirable: an application of pattern recognition, image processing and machine learning algorithms. Int. J. Eng. Technol. (2018). https://doi.org/10.14419/ijet.v7i1.2.9043

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1. Maize leaf disease recognition using PRF-SVM integration: a breakthrough technique;Scientific Reports;2024-05-03

2. A Fine-Tuned DenseNet Model for an Efficient Maize Leaf Disease Classification;2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2024-03-14

3. Combining Spatial and Temporal Analysis: A CNN-LSTM Hybrid Model for Maize Disease Classification;2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT);2024-02-09

4. An Early and Smart Detection of Corn Plant Leaf Diseases Using IoT and Deep Learning Multi-Models;IEEE Access;2024

5. Ensemble Based ERDNet model for Leaf Disease Detection in Rice and Maize Crops;2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS);2023-04-05

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