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International Conference on Ubiquitous Information Technologies and Applications

International Conference on Computer Science and its Applications

CUTE 2018, CSA 2018: Advances in Computer Science and Ubiquitous Computing pp 153–158Cite as

Performance Improvement on Object Detection for the Specific Domain Object Detecting

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 536))

Abstract

Currently, various studies are underway to improve the performance of Object Detection technology. In the proposed system, rather than classifying all fields as a whole, we want to check the performance of the domain by performing additional learning on the specific domain. In this paper, we propose the performance improvement in the object detection system for detecting human in the coastal image that shot by drone.

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References

  1. Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, D., Berg, A.C.: SSD: single shot multibox detector. In: Computer Vision-ECCV 2016. LNCS, vol. 9905, pp. 21–37 (2016)

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  2. Redmon, J., Farhadi, A.: YOLO9000: better, faster, stronger. arXiv:1612.08242 (2016)

  3. Choi, H., Kim, S., Bae, G., Noh, Y., Lee, D.: Real-time object recognition and reporting system. In: Korea Software Congress 2017, pp. 2107–2109 (2017)

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  4. Lee, J., Kim, D., Kim, J.: CPU-based YOLO performance enhancement technique for CCTV real-time object detection. In: Korea Computer Congress 2018, pp. 870–872 (2018)

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Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF2017R1D1A1B03030033).

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Authors and Affiliations

  1. Department of Computer Engineering, Pukyong National University, Busan, Republic of Korea

    Hyungi Hong & Mokdong Chung

Authors
  1. Hyungi Hong
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  2. Mokdong Chung
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Corresponding author

Correspondence to Mokdong Chung .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    James J. Park

  2. Department of Computer Software Engineering, Soon Chun Hyang University, Asan, Korea (Republic of)

    Doo-Soon Park

  3. Department of Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Young-Sik Jeong

  4. Department of Computer Science, Georgia State University, Atlanta, GA, USA

    Yi Pan

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Cite this paper

Hong, H., Chung, M. (2020). Performance Improvement on Object Detection for the Specific Domain Object Detecting. In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_26

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  • DOI: https://doi.org/10.1007/978-981-13-9341-9_26

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9340-2

  • Online ISBN: 978-981-13-9341-9

  • eBook Packages: EngineeringEngineering (R0)

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