Gaussian Kernel Based Classification Approach for Wheat Identification

6 citations as recorded by crossref.

1. A Novel Approach for Mapping Wheat Areas Using High Resolution Sentinel-2 Images A. Nasrallah et al. https://doi.org/10.3390/s18072089
2. Novel 3-D Deep Neural Network Architecture for Crop Classification Using Remote Sensing-Based Hyperspectral Images M. Ashraf et al. https://doi.org/10.1109/JSTARS.2024.3422078
3. Spatio-Temporal Monitoring of Shifting Cultivation Using Landsat Images: Soft Classification Approach G. Venkata Rao et al. https://doi.org/10.1007/s12524-018-0770-6
4. Identification of Paddy Stubble Burnt Activities Using Temporal Class-Based Sensor-Independent Indices Database: Modified Possibilistic Fuzzy Classification Approach A. Singh & A. Kumar https://doi.org/10.1007/s12524-019-01093-4
5. Wheat Monitoring by Using Kernel Based Possibilistic c-Means Classifier: Bi-sensor Temporal Multi-spectral Data R. Tripathi et al. https://doi.org/10.1007/s12524-016-0651-9
6. A fuzzy machine learning approach for identification of paddy stubble burnt fields K. Chhapariya et al. https://doi.org/10.1007/s41324-020-00356-4