APPLICATION OF TEMPORAL CONVOLUTIONAL NEURAL NETWORK FOR THE CLASSIFICATION OF CROPS ON SENTINEL-2 TIME SERIES

7 citations as recorded by crossref.

1. Channel Attention-Based Temporal Convolutional Network for Satellite Image Time Series Classification P. Tang et al. 10.1109/LGRS.2021.3095505
2. Dilated-RNNs: A Deep Approach for Continuous Volcano-Seismic Events Recognition M. Titos et al. 10.1109/JSTARS.2024.3421921
3. Multi-task hybrid spectral–spatial temporal convolution networks for classification of agricultural crop types and growth stages using drone-borne hyperspectral and multispectral images B. Chaudhury et al. 10.1117/1.JRS.17.038503
4. Attention-Aware Dynamic Self-Aggregation Network for Satellite Image Time Series Classification W. Zhang et al. 10.1109/TGRS.2021.3120914
5. Bi-modal contrastive learning for crop classification using Sentinel-2 and Planetscope A. Patnala et al. 10.3389/frsen.2024.1480101
6. Land cover classification using Land Parcel Identification System (LPIS) data and open source Eo-Learn library F. Şimşek & S. Durduran 10.1080/10106049.2022.2146760
7. Deep Learning for Satellite Image Time-Series Analysis: A review L. Miller et al. 10.1109/MGRS.2024.3393010