EXAMINATION OF A UAV IMAGE CLASSIFICATION METHOD BY USING MACHINE LEARNING AND WAVELET TRANSFORM

Author:

MOMOSE Akito1,MIYAMOTO Hitoshi2,IWAMI Shuji3,NAGAYA Takayuki3

Affiliation:

1. CTI Engineering Co., Ltd., Former graduate student, Shibaura Institute of Technology

2. Department of Civil Engineering, Shibaura Institute of Technology

3. CTI Engineering Co., Ltd.

Publisher

Japan Society of Civil Engineers

Subject

Civil and Structural Engineering,Environmental Engineering

Reference17 articles.

1. 1) Miyamoto, H., Akamatsu, Y. and Toda, Y. : Current status and future prospects for research on riverine forest issues, Advances in River Engineering, Vol. 19, pp. 441-446, 2013 (in Japanese).

2. 2) JSCE Committee on Hydroscience and Hydraulic Engineering, Subcommittee on Environmental Hydraulics, eds.: Environmental Hydraulics, Chap. 6.3., Riverine forestation, pp. 233–230, JSCE, 2015 (in Japanese).

3. 3) Franklin, S. E., Ahmed, O. S. and Williams, G. : Northern conifer forest species classification using multispectral data acquired from an unmanned aerial vehicle, Photogrammetric Engineering & Remote Sensing, Vol. 83(7), pp. 501–507, 2017.

4. 4) Suzuki, T., Tsuchiya, T., Suzuki, S. and Yamaba, A. : Vegetation classification using a small UAV based on superpixel segmentation and machine learning, Journal of the Remote Sensing Society of Japan, Regular Papers, Vol. 36, pp. 59–71, 2016 (in Japanese).

5. 5) Saito, M., Wakuda, Y., Ichikawa, K., Amaya, K., Nasuno, A., Oishi, T., Ikeuchi, K. and Ishikawa, Y. : Development of river channel maintenance via automatic discrimination of vegetation using UAV and deep learning, Journal of JSCE, Ser. B1 (Hydraulic Engineering), Vol. 74(4), pp. I_829–I_834, 2018 (in Japanese).

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