Deep learning applied to plant pathology: the problem of data representativeness
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s40858-021-00459-9.pdf
Reference64 articles.
1. Argüeso D, Picon A, Irusta U, Medela A, San-Emeterio MG, Bereciartua A, Alvarez-Gila A (2020) Few-Shot Learning approach for plant disease classification using images taken in the field. Computers and Electronics in Agriculture 175:105542
2. Badrinarayanan V, Kendall A, Cipolla R (2015) SegNet: a deep convolutional encoder-decoder architecture for image segmentation. arXiv 1511.00561
3. Barbedo JGA (2013) Digital image processing techniques for detecting, quantifying and classifying plant diseases. Springerplus 2:660
4. Barbedo JGA (2017) A new automatic method for disease symptom segmentation in digital photographs of plant leaves. European Journal of Plant Pathology 147:349–364
5. Barbedo JGA (2018a) Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification. Computers and Electronics in Agriculture 153:46–53
Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Effect of different weight initialization strategies on transfer learning for plant disease detection;Plant Pathology;2024-09-02
2. From Detection to Protection: The Role of Optical Sensors, Robots, and Artificial Intelligence in Modern Plant Disease Management;Phytopathology®;2024-08
3. Multi-level Banana Plant Disease Diagnosis with Score and Model Fusion;2024 International Conference on Control, Automation and Diagnosis (ICCAD);2024-05-15
4. Deep Learning Approaches for Plant Diseases Identification and Classification: A Comprehensive Review;2024 8th International Conference on Image and Signal Processing and their Applications (ISPA);2024-04-21
5. A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing;Computers and Electronics in Agriculture;2024-02
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3