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Remote Sensing Image Semantic Segmentation Method Based on a Deep Convolutional Neural Network and Multiscale Feature Fusion

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  • Guangzhen Zhang

    (The First Institute of Surveying and Mapping of Xinjiang Uygur Autonomous Region, China)

  • Wangyang Jiang

    (Second Institute of Aerial Remote Sensing MNR, Harbin, China)

Abstract

There are many problems with remote sensing images, such as large data scales, complex illumination conditions, occlusion, and dense targets. The existing semantic segmentation methods for remote sensing images are not accurate enough for small and irregular target segmentation results, and the edge extraction results are poor. The authors propose a remote sensing image segmentation method based on a DCNN and multiscale feature fusion. Firstly, an end-to-end remote sensing image segmentation model using complete residual connection and multiscale feature fusion was designed based on a deep convolutional encoder–decoder network. Secondly, weighted high-level features were obtained using an attention mechanism, which better preserved the edges, texture, and other information of remote sensing images. The experimental results on ISPRS Potsdam and Urban Drone datasets show that compared with the comparison methods, this method has better segmentation effect on small and irregular objects and achieves the best segmentation performance while ensuring the computation speed.

Suggested Citation

  • Guangzhen Zhang & Wangyang Jiang, 2023. "Remote Sensing Image Semantic Segmentation Method Based on a Deep Convolutional Neural Network and Multiscale Feature Fusion," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 19(1), pages 1-16, January.
  • Handle: RePEc:igg:jswis0:v:19:y:2023:i:1:p:1-16
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    1. Gupta, Brij B. & Gaurav, Akshat & Panigrahi, Prabin Kumar & Arya, Varsha, 2023. "Analysis of artificial intelligence-based technologies and approaches on sustainable entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    2. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    3. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    4. Martin Obschonka & David B. Audretsch, 2020. "Artificial intelligence and big data in entrepreneurship: a new era has begun," Small Business Economics, Springer, vol. 55(3), pages 529-539, October.
    5. Burström, Thommie & Parida, Vinit & Lahti, Tom & Wincent, Joakim, 2021. "AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research," Journal of Business Research, Elsevier, vol. 127(C), pages 85-95.
    6. Mohammed Banu Ali, 2019. "Multiple Perspective of Cloud Computing Adoption Determinants in Higher Education a Systematic Review," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 9(3), pages 89-109, July.
    7. Sergii Bogachov & Aleksy Kwilinski & Boris Miethlich & Viera Bartosova & Aleksandr Gurnak, 2020. "Artificial intelligence components and fuzzy regulators in entrepreneurship development," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 487-499, December.
    8. Yihang Cheng & Xi Zhang & Xiaojiong Wang & Hongke Zhao & Yao Yu & Xianhai Wang & Patricia Ordoñez de Pablos, 2021. "Rethinking the Development of Technology-Enhanced Learning and the Role of Cognitive Computing," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 17(1), pages 67-96, January.
    9. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
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