상세정보
학술대회
Architecture for Fast Object Detection Supporting CPU-GPU Hybrid and Distributed Computing
- 발행일
- 201701
- 출처
- International Conference on Consumer Electronics (ICCE) 2017, pp.149-150
- 협약과제
- 16MS2400, (1세부) 실시간 대규모 영상 데이터 이해·예측을 위한 고성능 비주얼 디스커버리 플랫폼 개발, 박경
- 초록
- This paper describes architecture for fast object detection that integrates uniform local binary patterns (ULBP) with convolutional neural networks (CNN). The proposed architecture also supports CPU-GPU hybrid and distributed computing based on the Hadoop distributed computing platform considering large-scale image big data.
- KSP 제안 키워드
- Big Data, CPU-GPU, Computing platform, Convolution neural network(CNN), Large scale image, Local binary Pattern, Object detection, distributed computing