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An efficient deep learning platform for detecting objects
- Authors
- Lee, H.; Kim, Y.; Park, J.W.; Shin, S.Y.; Hong, J.
- Issue Date
- Apr-2019
- Publisher
- Association for Computing Machinery
- Keywords
- Convolutional Neural Network; Object Detection; Object Recognition
- Citation
- Proceedings of the ACM Symposium on Applied Computing, v.Part F147772, pp.1353 - 1354
- Journal Title
- Proceedings of the ACM Symposium on Applied Computing
- Volume
- Part F147772
- Start Page
- 1353
- End Page
- 1354
- ISSN
- 0000-0000
- Abstract
- 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).
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Related Researcher
- Hong, Jiman
- College of Information Technology (School of Computer Science and Engineering)