Importance of individual sample of training data in modified possibilistic c-means classifier for handling heterogeneity within a specific crop
Author:
Affiliation:
1. University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha Unive
2. Indian Institute of Remote Sensing, Dehradun, Uttrakhand
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Earth and Planetary Sciences
Cited by 10 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
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2. Classifying Pinus roxburghii Using an Innovative Training Approach of Fuzzy Models While Handling Heterogeneity Within Class in Western Himalayan Forests;Journal of the Indian Society of Remote Sensing;2024-05-18
3. Fuzzy machine learning model to detect transition building footprints using multi-sensor multi-temporal images;Remote Sensing Applications: Society and Environment;2024-04
4. Fuzzy machine learning model for class-based flood damage assessment from planetscope temporal data;Journal of Applied Remote Sensing;2024-03-14
5. Vegetation Index-Based Classification of Pinus roxburghii and Quercus leucotricophora in Himalayan Temperate Forest Using Fuzzy Machine Learning Model;2023 IEEE India Geoscience and Remote Sensing Symposium (InGARSS);2023-12-10
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