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An efficient deep learning platform for detecting objects
- Lee, H.;
- Kim, Y.;
- Park, J.W.;
- Shin, S.Y.;
- Hong, J.
Citations
SCOPUS
0초록
Real-time object detection models based on deep learning are being studied. However, when using deep learning, the user must directly select one of the various object detection models, and the result of object detection may vary depending on the selected object detection model. Therefore, in this paper, we propose an efficient deep learning platform for object detection technology. The proposed platform estimates learning results based on benchmark results and recommends proper object detection model based on deep learning to minimizes user intervention. © 2019 Copyright is held by the owner/author(s).
키워드
Convolutional Neural Network; Object Detection; Object Recognition; Deep learning; E-learning; Neural networks; Object recognition; Convolutional neural network; Detecting objects; Detection models; Detection technology; Learning platform; Real time; User intervention; Object detection
- 제목
- An efficient deep learning platform for detecting objects
- 저자
- Lee, H.; Kim, Y.; Park, J.W.; Shin, S.Y.; Hong, J.
- 발행일
- 2019-04
- 유형
- Conference Paper
- 저널명
- Proceedings of the ACM Symposium on Applied Computing
- 권
- Part F147772
- 페이지
- 1353 ~ 1354
- 언어
- ENG
- 출판사
- Association for Computing Machinery
- 발행국가
- 미국
- 분량
- 2 페이지
- ISSN
- P 0000-0000