Browsing Institute of New Imaging Technologies (INIT) by Keyword "deep learning (DL)"
Now showing items 1-4 of 4
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Deep Unsupervised Embedding for Remotely Sensed Images Based on Spatially Augmented Momentum Contrast
IEEE (2020-07-14)Convolutional neural networks (CNNs) have achieved great success when characterizing remote sensing (RS) images. However, the lack of sufficient annotated data (together with the high complexity of the RS image domain) ... -
Low-High-Power Consumption Architectures for Deep-Learning Models Applied to Hyperspectral Image Classification
IEEE (2018-11)Convolutional neural networks have emerged as an excellent tool for remotely sensed hyperspectral image (HSI) classification. Nonetheless, the high computational complexity and energy requirements of these models typically ... -
Remote Sensing Image Superresolution Using Deep Residual Channel Attention
IEEE (2019-07-23)The current trend in remote sensing image superresolution (SR) is to use supervised deep learning models to effectively enhance the spatial resolution of airborne and satellite-based optical imagery. Nonetheless, the ... -
Remote Sensing Single-Image Superresolution Based on a Deep Compendium Model
IEEE (2019-03)This letter introduces a novel remote sensing single-image superresolution (SR) architecture based on a deep efficient compendium model. The current deep learning-based SR trend stands for using deeper networks to improve ...