Results 21 to 30 of about 2,902 (152)

O129 CLASSIFICATION OF BARRETT’S CARCINOMA SPECIMENS BY HYPERSPECTRAL IMAGING (HSI)

Diseases of the Esophagus, 2019
Abstract Aim Hyperspectral imaging (HSI) technology combines imaging with spectroscopy and can be used for the classification of malignant and non-malignant cells. Thereby HSI combined with artificial intelligent algorithms can be used to predict tumor cells in in Barrett’s carcinoma specimens.
Thieme René, Maktabi Marianne, Köhler Hannes, Chalopin Claire, Jansen-Winkeln Boris, Gockel Ines   +5 more
openaire   +1 more source

A Novel Analysis Dictionary Learning Model Based Hyperspectral Image Classification Method

Remote Sensing, 2019
Supervised hyperspectral image (HSI) classification has been acknowledged as one of the fundamental tasks of hyperspectral data analysis. Witnessing the success of analysis dictionary learning (ADL)-based method in recent years, we propose an ADL-based ...
Wei Wei, Mengting Ma, Cong Wang, Lei Zhang, Peng Zhang, Yanning Zhang   +5 more
doaj   +1 more source

A Lightweight 1-D Convolution Augmented Transformer with Metric Learning for Hyperspectral Image Classification

Sensors, 2021
Hyperspectral image (HSI) classification is the subject of intense research in remote sensing. The tremendous success of deep learning in computer vision has recently sparked the interest in applying deep learning in hyperspectral image classification ...
Xiang Hu, Wenjing Yang, Hao Wen, Yu Liu, Yuanxi Peng   +4 more
doaj   +1 more source

Cross-Scene Deep Transfer Learning With Spectral Feature Adaptation for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
The small size of labeled samples has always been one of the great challenges in hyperspectral image (HSI) classification. Recently, cross-scene transfer learning has been developed to solve this problem by utilizing auxiliary samples of a relevant scene.
Chongxiao Zhong, Junping Zhang, Sifan Wu, Ye Zhang   +3 more
doaj   +1 more source

Adversarial Representation Learning for Hyperspectral Image Classification with Small-Sized Labeled Set

Remote Sensing, 2022
Hyperspectral image (HSI) classification is one of the main research contents of hyperspectral technology. Existing HSI classification algorithms that are based on deep learning use a large number of labeled samples to train models to ensure excellent ...
Shuhan Zhang, Xiaohua Zhang, Tianrui Li, Hongyun Meng, Xianghai Cao, Li Wang   +5 more
doaj   +1 more source

Hyperspectral Image Classification with Multi-Scale Feature Extraction

Remote Sensing, 2019
Spectral features cannot effectively reflect the differences among the ground objects and distinguish their boundaries in hyperspectral image (HSI) classification.
Bing Tu, Nanying Li, Leyuan Fang, Danbing He, Pedram Ghamisi   +4 more
doaj   +1 more source

Feature Extraction Based Multi-Structure Manifold Embedding for Hyperspectral Remote Sensing Image Classification

IEEE Access, 2017
Hyperspectral remote sensing image is a typical high-dimensional data with a large number of redundant information, which will impact the classification accuracy.
Yuhang Gan, Fulin Luo, Juhua Liu, Bing Lei, Tao Zhang, Ke Liu   +5 more
doaj   +1 more source

Classification of hyperspectral images via improved cycle‐MLP

IET Computer Vision, 2022
Pixel‐wise classification of hyperspectral image (HSI) is a hot spot in the field of remote sensing. The classification of HSI requires the model to be more sensitive to dense features, which is quite different from the modelling requirements of ...
Na Gong, Chunlei Zhang, Heng Zhou, Kai Zhang, Zhongyuan Wu, Xin Zhang   +5 more
doaj   +1 more source

Mapping Coastal Wetlands Using Transformer in Transformer Deep Network on China ZY1-02D Hyperspectral Satellite Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Coastal wetlands mapping is a big challenge in remote sensing fields because of similar spectrum of different ground objects and their severe fragmentation and spatial heterogeneity.
Kai Liu, Weiwei Sun, Yijun Shao, Weiwei Liu, Gang Yang, Xiangchao Meng, Jiangtao Peng, Dehua Mao, Kai Ren   +8 more
doaj   +1 more source

Land use/land cover (LULC) classification using hyperspectral images: a review

Geo-spatial Information Science
In the rapidly evolving realm of remote sensing technology, the classification of Hyperspectral Images (HSIs) is a pivotal yet formidable task. Hindered by inherent limitations in hyperspectral imaging, enhancing the accuracy and efficiency of HSI ...
Chen Lou, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Abdelghani Dahou, Mohamed Abd Elaziz, Laith Abualigah, Ahmed A. Ewees   +6 more
doaj   +1 more source