Apr 22, 2022 · Im-BiLSTM model jointly performs missing data imputation and crop classification. •. Im-BiLSTM model classification outperforms BiLSTM model. •.

Multi-temporal deep learning approaches can make full use of crop growth patterns and phenological characteristics, resulting in excellent crop classification ...

A joint learning Im-BiLSTM model for incomplete time-series Sentinel-2A data imputation and crop classification. https://doi.org/10.1016/j.jag.2022.102762.

Adversarial Joint-learning Recurrent Neural Network (AJ-RNN) is an end-to-end model trained in an adversarial and joint learning manner. It can impute missing ...

Jun 30, 2024 · This study proposes a framework based on an attention Bidirectional Long Short-Term Memory (BiLSTM) network for predicting multiband images.

Feb 15, 2024 · This paper presents a model framework for the imputation and classification of missing small sample time series data.

A joint learning Im-BiLSTM model for incomplete time-series Sentinel-2A data imputation and crop classification. Article. Full-text available. Apr 2022; INT J ...

Chen et al. A joint learning Im-BiLSTM model for incomplete time-series Sentinel-2A data imputation and crop classification. International Journal of Applied ...

A joint learning Im-BiLSTM model for incomplete time-series Sentinel-2A data imputation and crop classification. Int. J. Appl. Earth Obs. Geoinf. 2022, 108 ...

A joint learning Im-BiLSTM model for incomplete time-series Sentinel-2A data imputation and crop classification. Request PDF. Open Access. International ...