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Article

A High-Accuracy Model Average Ensemble of Convolutional Neural Networks for Classification of Cloud Image Patches on Small Datasets

Department of Computer Engineering, Hanbat National University, Daejeon 34158, Korea
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Appl. Sci. 2019, 9(21), 4500; https://doi.org/10.3390/app9214500
Received: 11 September 2019 / Revised: 20 October 2019 / Accepted: 21 October 2019 / Published: 23 October 2019
(This article belongs to the Special Issue Machine Learning Techniques Applied to Geospatial Big Data)
Research on clouds has an enormous influence on sky sciences and related applications, and cloud classification plays an essential role in it. Much research has been conducted which includes both traditional machine learning approaches and deep learning approaches. Compared with traditional machine learning approaches, deep learning approaches achieved better results. However, most deep learning models need large data to train due to the large number of parameters. Therefore, they cannot get high accuracy in case of small datasets. In this paper, we propose a complete solution for high accuracy of classification of cloud image patches on small datasets. Firstly, we designed a suitable convolutional neural network (CNN) model for small datasets. Secondly, we applied regularization techniques to increase generalization and avoid overfitting of the model. Finally, we introduce a model average ensemble to reduce the variance of prediction and increase the classification accuracy. We experiment the proposed solution on the Singapore whole-sky imaging categories (SWIMCAT) dataset, which demonstrates perfect classification accuracy for most classes and confirms the robustness of the proposed model. View Full-Text
Keywords: cloud classification; CNN; ensemble model; SWIMCAT dataset cloud classification; CNN; ensemble model; SWIMCAT dataset
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MDPI and ACS Style

Phung, V.H.; Rhee, E.J. A High-Accuracy Model Average Ensemble of Convolutional Neural Networks for Classification of Cloud Image Patches on Small Datasets. Appl. Sci. 2019, 9, 4500. https://doi.org/10.3390/app9214500

AMA Style

Phung VH, Rhee EJ. A High-Accuracy Model Average Ensemble of Convolutional Neural Networks for Classification of Cloud Image Patches on Small Datasets. Applied Sciences. 2019; 9(21):4500. https://doi.org/10.3390/app9214500

Chicago/Turabian Style

Phung, Van H., and Eun J. Rhee 2019. "A High-Accuracy Model Average Ensemble of Convolutional Neural Networks for Classification of Cloud Image Patches on Small Datasets" Applied Sciences 9, no. 21: 4500. https://doi.org/10.3390/app9214500

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