DEEP LEARNING FOR REMOTE SENSING IMAGE CLASSIFICATION FOR AGRICULTURE APPLICATIONS

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1. INTELLIGENT ACQUISITION METHOD OF HERBACEOUS FLOWERS IMAGE BASED ON THEME CRAWLER, DEEP LEARNING AND GAME THEORY Z. Xie et al. https://doi.org/10.52013/2658-7556-66-4-12
2. APPLICATION OF FUZZY METRICS IN CLUSTERING PROBLEMS OF AGRICULTURAL CROP VARIETIES A. Stamenković et al. https://doi.org/10.59267/ekoPolj2401121S
3. Comparative Analysis of Deep Learning and Traditional Methods for High-Resolution Cropland Extraction with Different Training Data Characteristics D. Zhang et al. https://doi.org/10.3390/land14102038
4. Classification of Citrus Canker and Black Spot Diseases using a Deep Learning based Approach G. Adeem et al. https://doi.org/10.21015/vtess.v15i3.976
5. Unsupervised remote sensing image thin cloud removal method based on contrastive learning Z. Tan et al. https://doi.org/10.1049/ipr2.13067
6. Satellite Video Remote Sensing for Flood Model Validation C. Masafu & R. Williams https://doi.org/10.1029/2023WR034545
7. Measurement of Fracture Networks in Rock Sample by X-Ray Tomography, Convolutional Filtering and Deep Learning A. Caputo et al. https://doi.org/10.3390/s25144409
8. A Comprehensive Review of Deep Learning-Based Anomaly Detection Methods for Precision Agriculture K. Gkountakos et al. https://doi.org/10.1109/ACCESS.2024.3522248
9. Leveraging Deep Learning in Remote Sensing: A Novel Approach for Agricultural Greenhouse Detection and Innovation Management V. Tomco et al. https://doi.org/10.26833/ijeg.1587264
10. A novel machine learning approach to classify the remote sensing optically images based on swarm intelligence Y. Xiong & T. Zhang https://doi.org/10.1007/s11082-023-04989-1
11. MASPP and MWASP: multi-head self-attention based modules for UNet network in melon spot segmentation K. Tran et al. https://doi.org/10.1007/s11694-024-02466-1
12. A Novel Enhanced VGG16 Model to Tackle Grapevine Leaves Diseases With Automatic Method S. Mousavi & G. Farahani https://doi.org/10.1109/ACCESS.2022.3215639
13. Deep Learning Based Mineral Image Classification Combined With Visual Attention Mechanism Y. Liu et al. https://doi.org/10.1109/ACCESS.2021.3095368
14. A comprehensive systematic review of deep learning methods for hyperspectral images classification P. Ranjan & A. Girdhar https://doi.org/10.1080/01431161.2022.2133579
15. Agricultural Text Classification Method Based on Dynamic Fusion of Multiple Features Y. Li et al. https://doi.org/10.1109/ACCESS.2023.3253386
16. Automated weed monitoring and control: enhancing detection accuracy using a YOLOv7-AlexNet fusion network M. Faizan Zeb et al. https://doi.org/10.3389/fpls.2025.1664650