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Deep Learning-based Real-time Segmentation for Edge Computing Devices
- Kwak, Jaeho;
- Yu, Hyunwoo;
- Cho, Yubin;
- Kang, Sukju;
- Cho, Jaechan;
- 외 2명
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0초록
Recently, due to the rapid improvement of artificial intelligence technology, numerous studies are considered to solve various problems using deep learning. Typical deep neural networks for semantic segmentation require the high computation with a large capacity to extract abundant amounts of contextual information for accurate prediction. Our live demonstration will show real-time semantic segmentation operation on an NVIDIA Jetson-Xavier board with the BiSeNet-based method compressed using a novel knowledge distillation method.
키워드
deep learning; semantic segmentation; real-time processing
- 제목
- Deep Learning-based Real-time Segmentation for Edge Computing Devices
- 저자
- Kwak, Jaeho; Yu, Hyunwoo; Cho, Yubin; Kang, Sukju; Cho, Jaechan; Park, Jun-Young; Lee, Ji-Won
- 발행일
- 2022-06
- 유형
- Proceedings Paper
- 저널명
- 2022 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2022): INTELLIGENT TECHNOLOGY IN THE POST-PANDEMIC ERA