DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sung, M. | - |
dc.contributor.author | CHO, HYEONWOO | - |
dc.contributor.author | JASON, KIM | - |
dc.contributor.author | Yu, S.-C. | - |
dc.date.accessioned | 2022-06-22T08:40:23Z | - |
dc.date.available | 2022-06-22T08:40:23Z | - |
dc.date.created | 2022-05-03 | - |
dc.date.issued | 2019-04-19 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/112999 | - |
dc.description.abstract | Sonar sensor is widely used for underwater object recognition. However, acquiring reference sonar images for each target object is high-cost and time-consuming. Sonar image simulators can generate reference sonar images with small computation, but the simulated images are different with actual sonar images captured in the field. This paper proposes a method to translate actual sonar images to simulated-like images using a generative adversarial network. We trained the network with images captured by the indoor water tank test. The trained neural network can generate simulator-like images from given actual sonar images. Further, we can recognize the target object using template matching between the translated image and the reference images simulating the target object. © 2019 IEEE. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.relation.isPartOf | 2019 IEEE International Underwater Technology Symposium, UT 2019 | - |
dc.relation.isPartOf | 2019 IEEE International Underwater Technology Symposium, UT 2019 - Proceedings | - |
dc.title | Sonar Image Translation Using Generative Adversarial Network for Underwater Object Recognition | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.identifier.bibliographicCitation | 2019 IEEE International Underwater Technology Symposium, UT 2019, pp.1 - 6 | - |
dc.citation.conferenceDate | 2019-04-16 | - |
dc.citation.conferencePlace | CH | - |
dc.citation.conferencePlace | NATIONAL SUN YAT-SEN UNIVERSITY | - |
dc.citation.endPage | 6 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | 2019 IEEE International Underwater Technology Symposium, UT 2019 | - |
dc.contributor.affiliatedAuthor | Sung, M. | - |
dc.contributor.affiliatedAuthor | CHO, HYEONWOO | - |
dc.contributor.affiliatedAuthor | JASON, KIM | - |
dc.contributor.affiliatedAuthor | Yu, S.-C. | - |
dc.identifier.scopusid | 2-s2.0-85068439321 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
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