An Intelligent Deep Learning Based Xception Model for Hyperspectral Image Analysis and Classification
Source abstract
Abstract
Due to the advancements in remote sensing technologies, the generation of hyperspectral imagery (HSI) gets significantly increased. Accurate classification of HSI becomes a critical process in the domain of hyperspectral data... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Remote-Sensing Image Classification · Smart Agriculture and AI · Currency Recognition and Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (24)
Show source-provided references
1. Investigation of epifauna coverage on seagrass blades using spatial and spectral analysis of hyperspectral images
2. Semisupervised neural networks for efficient hyperspectral image classification10.1109/TGRS.2009.2037898 ↗
3. Reducing the dimensionality of data with neural networks10.1126/science.1127647 ↗
4. Semisupervised stacked autoencoder with cotraining for hyperspectral image classification10.1109/TGRS.2018.2888485 ↗
5. Hyperspectral image classification using feature relations map learning10.3390/rs12182956 ↗
6. Deep learning-based classification of hyperspectral data10.1109/JSTARS.2014.2329330 ↗
7. Spectral–spatial classification of hyperspectral data based on deep belief network10.1109/JSTARS.2015.2388577 ↗
8. Convolutional neural networks based hyperspectral image classification method with adaptive kernels10.3390/rs9060618 ↗
9. Convolutional recurrent neural networks for hyperspectral data classification10.3390/rs9030298 ↗
10. Hyperspectral image classification using deep pixel-pair features10.1109/TGRS.2016.2616355 ↗
11. A new deep-learning-based hyperspectral image classification method10.1109/JSTARS.2017.2655516 ↗
12. Diverse region-based CNN for hyperspectral image classification10.1109/TIP.2018.2809606 ↗
13. A classifier ensemble based on fusion of support vector machines for classifying hyperspectral data10.1080/19479832.2010.485935 ↗
14. An SVM ensemble approach combining spectral, structural, and semantic features for the classification of high-resolution remotely sensed imagery10.1109/TGRS.2012.2202912 ↗
15. Sample-screening MKL method via boosting strategy for hyperspectral image classification10.1016/j.neucom.2015.09.035 ↗
16. Feature selection and multiple kernel boosting framework based on PSO with mutation mechanism for hyperspectral classification10.1016/j.neucom.2016.05.103 ↗
17. Multi-model LSTM-based convolutional neural networks for detection of apple diseases and pests
18. Very deep convolutional neural networks for complex land cover mapping using multispectral remote sensing imagery10.3390/rs10071119 ↗
19. Spectral–spatial hyperspectral image classification with superpixel pattern and extreme learning machine
20. Design IIR digital filters using quantum-behaved particle swarm optimization10.1007/11802914_51 ↗
21. Quantum behaved particle swarm optimization algorithm based on artificial fish swarm
22. “The Real HYDICE Urban Hyperspectral Dataset. Available online: http://lesun.weebly.com/hyperspectraldata-set.html (accessed on 13 June 2019).
23. Deep convolutional neural networks for hyperspectral image classification10.1155/2015/258619 ↗
24. Semi-supervised hyperspectral image classification via spatial-regulated self-training