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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제17권 제5호
- 발행연도
- 2021.10
- 수록면
- 892 - 904 (13page)
- DOI
- 10.3745/JIPS.02.0164
이용수
초록· 키워드
오류제보하기
An image semantic segmentation model is proposed based on improved ENet network in order to achieve the
low accuracy of image semantic segmentation in complex environment. Firstly, this paper performs pruning
and convolution optimization operations on the ENet network. That is, the network structure is reasonably
adjusted for better results in image segmentation by reducing the convolution operation in the decoder and
proposing the bottleneck convolution structure. Squeeze-and-excitation (SE) module is then integrated into the
optimized ENet network. Small-scale targets see improvement in segmentation accuracy via automatic learning
of the importance of each feature channel. Finally, the experiment was verified on the public dataset. This
method outperforms the existing comparison methods in mean pixel accuracy (MPA) and mean intersection
over union (MIOU) values. And in a short running time, the accuracy of the segmentation and the efficiency of
the operation are guaranteed.
목차
등록된 정보가 없습니다.
참고문헌 (31)
참고문헌 신청
R. Moreno / 2012 / Image segmentation on spherical coordinate representation of RGB colour space / IET Image Processing 6(9):1275~1283
Z. C. Jing / 2018 / A geometric flow approach for region-based image segmentation-theoretical analysis / Acta Mathematicae Applicatae Sinica, English Series 34(1):65~76
L. C. Chen / 2017 / DeepLab : semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFS / IEEE Transactions on Pattern Analysis and Machine Intelligence 40(4):834~848
T. Ling / 2019 / An image segmentation algorithm using visual saliency and graph cut / Paper Asia 2(1):114~118
A. V. Anjikar / 2019 / Color image segmentation using region growth and merge improved technique / International Journal of Computer Sciences and Engineering 7(3):1070~1072
Z. C. Jing / 2018 / A geometric flow approach for region-based image segmentation-theoretical analysis / Acta Mathematicae Applicatae Sinica, English Series 34(1):65~76
L. C. Chen / 2017 / DeepLab : semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFS / IEEE Transactions on Pattern Analysis and Machine Intelligence 40(4):834~848
T. Ling / 2019 / An image segmentation algorithm using visual saliency and graph cut / Paper Asia 2(1):114~118
A. V. Anjikar / 2019 / Color image segmentation using region growth and merge improved technique / International Journal of Computer Sciences and Engineering 7(3):1070~1072
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