230 lines
8.9 KiB
Plaintext
230 lines
8.9 KiB
Plaintext
<!DOCTYPE html>
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<html lang="eng">
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<meta name="description" content="주식회사 디비엔텍의 홈페이지입니다.">
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<p class="toggle">버튼</p>
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<h1><a href="/eng/index_eng.html">dbntect</a></h1>
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<a href="/eng/index_eng.html">HOME</a>
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<ul>
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<li>COMPANY<span>R&D</span></li>
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<li>Our R&D Plan</li>
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</ul>
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<div id="research"><!-- 임시 높이값 지정 추후 삭제-->
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<p style="cursor:default;">COMPANY <em>></em> <span><a href="#">R&D</a></span></p>
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<h2>
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Research & Develop
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</h2>
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<div class="threeTap">
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<ul class="clearfix">
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<li>< Deep-learning based incident detection system ></li>
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<li>< Bridge and facility physical examination system ></li>
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<li>< Lunar surface Crater detection system ></li>
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</ul>
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</div><!--end of threeTap-->
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<div class="research">
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<div class="research_01 bs_section">
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<ul class="clearfix">
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<li>img01</li>
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<li>
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<dl>
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<dt>01. Deep-learning based incident detection system</dt>
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<dd>
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Deep-learning based incident detection system is Automatically recognizes targets within range
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and Automaticlly alert and observing Emergency situation.
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Compared with computer vision based images analysis , It was less influenced by weather and region.
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Can recognized Accident more high accuracy.
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</dd>
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</dl>
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</li>
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</ul>
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</div>
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<div class="research_02 bs_section">
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<ul class="clearfix">
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<li style="float : right;">img01</li>
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<li class="pos_right">
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<dl>
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<dt>02. Bridge and facility physical examination system</dt>
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<dd>
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Social infrastructure in Korea has grown rapidly in the 1970s.
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Currently, facilities that are more than 30 years old account for about 10%, and in 2025 they will exceed 20%.
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So, maintenance costs for older facilities are increasing, and the need for a solution based on computer image
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recognition has been continuously raised for effective facility condition assessment and safety diagnosis.
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</dd>
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</dl>
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</li>
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</ul>
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</div>
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<div class="research_03 bs_section">
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<ul class="clearfix">
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<li>img01</li>
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<li>
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<dl>
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<dt>03. Lunar surface Crater detection system</dt>
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<dd>
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It is very important to collect terrain information based on images acquired from the lunar.
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in the lunar surface research. As the development of deep learning technology,
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research is being carried out to apply this technology to terrain information collection.
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We are in the process of studying image object segmentation together with KICT space construction research center group.
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</dl>
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</li>
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</ul>
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</div>
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</div><!--end of class certificate-->
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</div><!--end of #research-->
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<footer>
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<h1>dbntect</h1>
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<address>
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<dl>
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<!-- <dt>f_icon_1</dt> -->
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<dd>Email <a href="mailto:ahn@dbnt.co.kr">ahn@dbnt.co.kr</a></dd>
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</dl>
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<dd>Tel <a href="tel:+82-32-721-5670">+82.32.721.5670</a></dd>
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<dd>Fax <a href="#">+82.32.721.5680</a></dd>
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<dl>
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<dd>Location <a href="https://www.google.co.kr/maps/place/%EB%A1%9C%EB%B4%87%EB%9E%9C%EB%93%9C/@37.5181167,126.6047585,15.75z/data=!4m8!1m2!2m1!1z66Gc67SH656c65Oc66Gc!3m4!1s0x0:0xc3c41e97f713287c!8m2!3d37.5196316!4d126.610879?hl=ko" target="_blank">RobotTower, No. 1205, 155-11, Robot land-ro, Seo-gu,<span> Incheon, Republic of Korea</span></a></dd>
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Copyright 2018. DBNtech all rights reserved
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