Classification of hyperspectral images by deep learning of spectral-spatial features
Sign Up to like & getrecommendations! Published in 2020 at "Arabian Journal of Geosciences"
DOI: 10.1007/s12517-020-05487-4
Abstract: Creating accurate land use and land cover maps using remote sensing images is one of the most important applications of remotely sensed data. Abundant spectral information in hyperspectral images (HSI) makes it possible to distinguish… read more here.
Keywords: feature; spectral spatial; classification hyperspectral; spatial features ... See more keywords
Landslide susceptibility assessment using lightweight dense residual network with emphasis on deep spatial features
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-97074-4
Abstract: Landslides are among the geological disasters that frequently occur worldwide and significantly restrict the sustainable development of society. Therefore, it is of great practical significance to perform landslide susceptibility assessment. In addressing issues such as… read more here.
Keywords: deep spatial; susceptibility; landslide susceptibility; susceptibility assessment ... See more keywords
Temporal-Spatial Features of Intention Understanding Based on EEG-fNIRS Bimodal Measurement
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Access"
DOI: 10.1109/access.2017.2723428
Abstract: Understanding the actions of other people is a key component of social interaction. This paper used an electroencephalography and functional near infrared spectroscopy (EEG-fNIRS) bimodal system to investigate the temporal-spatial features of action intention understanding.… read more here.
Keywords: spatial features; fnirs bimodal; temporal spatial; eeg fnirs ... See more keywords
Spectral-Spatial Features Extraction of Hyperspectral Remote Sensing Oil Spill Imagery Based on Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3194260
Abstract: Marine oil spills accidents has caused a large amount of crude oil to leak into the marine environment and threaten marine ecological environment. Hyperspectral remote sensing images (HRSI) technology can quickly and accurately identify oil… read more here.
Keywords: neural networks; oil; spectral spatial; convolutional neural ... See more keywords
Hyperspectral Classification via Global-Local Hierarchical Weighting Fusion Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3133009
Abstract: The fusion of spectral–spatial features based on deep learning has become the focus of research in hyperspectral image (HSI) classification. However, previous deep frameworks based on spectral–spatial fusion usually performed feature aggregation only at the… read more here.
Keywords: fusion; classification; spectral spatial; spatial features ... See more keywords
Thin Cloud Removal Fusing Full Spectral and Spatial Features for Sentinel-2 Imagery
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3211857
Abstract: Multispectral remote sensing images are widely used for monitoring the globe. Although thin clouds can affect all optical bands, the influences of thin clouds differ with band wavelength. When processing multispectral bands at different resolutions,… read more here.
Keywords: spatial features; cloud removal; thin cloud; thin clouds ... See more keywords
On the Effect of Spatially Non-Disjoint Training and Test Samples on Estimated Model Generalization Capabilities in Supervised Classification With Spatial Features
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2747222
Abstract: In this letter, we establish two sampling schemes to select training and test sets for supervised classification. We do this in order to investigate whether estimated generalization capabilities of learned models can be positively biased… read more here.
Keywords: training test; generalization capabilities; model; spatial features ... See more keywords
Spatial Features Acquisition for Airplane Target Detection in Hyperspectral Remote Sensing Using Virtual RGB Images
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2024.3451691
Abstract: Hyperspectral target detection (HTD) stands as a pivotal research area within hyperspectral image (HSI) processing. Airplane is challenging to detect as small targets in HSI. There are problems of limited target labeled samples and insufficient… read more here.
Keywords: detection; target detection; virtual rgb; rgb images ... See more keywords
Spectral-Spatial Deep Support Vector Data Description for Hyperspectral Anomaly Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3144192
Abstract: Hyperspectral anomaly detection (HAD) aims to distinguish anomalies from background-by-background modeling. Deep learning has been applied to HAD and achieves promising detection results. However, there exist several issues that need to be addressed: 1) unrealistic… read more here.
Keywords: hyperspectral anomaly; spectral spatial; detection; spatial features ... See more keywords
Hyperspectral image secure retrieval based on encrypted deep spectral–spatial features
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.13.018501
Abstract: Abstract. With the rapid development of remote-sensing earth observation technology, hyperspectral imagery has shown exponential growth. The quick and accurate retrieval of hyperspectral images has become a practical challenge in applications. Moreover, open network sharing… read more here.
Keywords: deep spectral; retrieval; hyperspectral image; spatial features ... See more keywords
Unsupervised change detection for remotely sensed multi-spectral images based on context-aware saliency-spectral-spatial features and weighted coarse-to-fine fusion
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.18.046501
Abstract: Abstract. Saliency detection is a conventional computer vision technique used to identify salient regions in difference images for change detection (CD) in multi-temporal/bi-temporal remotely sensed images. However, most existing saliency-based CD methods have primarily focused… read more here.
Keywords: saliency; aware saliency; context aware; spectral spatial ... See more keywords