1D-CONVOLUTIONAL AUTOENCODER BASED HYPERSPECTRAL DATA COMPRESSION

8 citations as recorded by crossref.

1. Enhancing Feature Detection and Matching in Low-Pixel-Resolution Hyperspectral Images Using 3D Convolution-Based Siamese Networks C. Perera et al. 10.3390/s23188004
2. Adaptive Two-Stage Multisensor Convolutional Autoencoder Model for Lossy Compression of Hyperspectral Data J. Kuester et al. 10.1109/TGRS.2023.3328222
3. Comparative analysis of filtering methods for measurement data from complex well configurations D. Shengeliya et al. 10.21684/2411-7978-2024-10-2-104-120
4. An End-to-End Learning-Based Control Signal Prediction for Autonomous Robotic Colonoscopy V. Nguyen et al. 10.1109/ACCESS.2023.3340677
5. Enhancing data sparsity in spectral signals using wavelet decomposition for improved compression and storage efficiency H. Yang et al. 10.1016/j.yofte.2024.103848
6. Unsupervised fault detection using frequency-wise angular filtering in contaminated vibration signals Y. Byun et al. 10.1080/00207543.2024.2427895
7. Importance of Terrain and Climate for Predicting Soil Organic Carbon Is Highly Variable across Local to Continental Scales T. Tan et al. 10.1021/acs.est.4c01172
8. Onboard Deep Lossless and Near-Lossless Predictive Coding of Hyperspectral Images With Line-Based Attention D. Valsesia et al. 10.1109/TGRS.2024.3465043