The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Deep supervised learning for hyperspectral data classification through convolutional neural networks
Abstract
Spectral observations along the spectrum in many narrow spectral bands through hyperspectral imaging provides valuable information towards material and object recognition, which can be consider as a classification task. Most of the existing studies and research efforts are following the conventional pattern recognition paradigm, which is based on the construction of complex handcrafted features. However, it is rarely known which features are important for the problem at hand. In contrast to these approaches, we propose a deep learning based classification method that hierarchically constructs high-level features in an automated way. Our method exploits a Convolutional Neural Network to encode pixels' spectral and spatial information and a Multi-Layer Perceptron to conduct the classification task. Experimental results and quantitative validation on widely used datasets showcasing the potential of the developed approach for accurate hyperspectral data classification.
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Cites
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Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources
Zhu, X. X., Tuia, D., Mou, L., Xia, G.-S., Zhang, L., Xu, F., & Fraundorfer, F. (2017) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2017.2762307 · Cited by 3,400
Deep Learning for Hyperspectral Image Classification: An Overview
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Convolutional neural networks for large-scale remote-sensing image classification
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Surface Water Mapping by Deep Learning
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A comprehensive survey of deep learning-based lightweight object detection models for edge devices
Mittal, P. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10877-1 · Cited by 244
Limited effects of tree planting on forest canopy cover and rural livelihoods in Northern India
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DeepLab-Based Spatial Feature Extraction for Hyperspectral Image Classification
Niu, Z., Liu, W., Zhao, J., & Jiang, G. (2019) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2018.2871507 · Cited by 86
Time Series Data for Equipment Reliability Analysis With Deep Learning
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Capsulenet-Based Spatial–Spectral Classifier for Hyperspectral Images
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Self-citation
Metadata
- Authors
- Makantasis, K., Karantzalos, K., Doulamis, A., & Doulamis, N.
- Venue
- 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
- Publisher
- IEEE
- Published
- 2015-07
- Pages
- 4959-4962
- OpenAlex
- W1966580635
- Cited by
- 1,011
- References
- 5
- FWCI
- 84.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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