뉴럴 네트워크를 이용한 수중 이미지에서의 실시간 물고기 인식 방법
- Title
- 뉴럴 네트워크를 이용한 수중 이미지에서의 실시간 물고기 인식 방법
- Authors
- YU, SON CHEOL; MINSUNG, SUNG
- Date Issued
- 2017-11-30
- Publisher
- 한국수중·수상로봇기술연구회
- Abstract
- CNN composed of 24 convolutional layers and two fully-connected layers. We then trained the CNN with custom
fish images. Actual fish images and videos are used to train and evaluate the CNN. The CNN recorded 93% detection
accuracy and ran at 16.7 frames per second (FPS). The proposed method can detect fish in dim, noisy, and hazy underwater
optical images precisely and accurately in a real time without preprocessing of images
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/41686
- Article Type
- Conference
- Citation
- 2017 한국수중수상로봇기술연구회 추계학술대회, page. 1 - 3, 2017-11-30
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.