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Volumn 2018-April, Issue , 2018, Pages 1421-1429

DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics

Author keywords

[No Author keywords available]

Indexed keywords

AUGMENTED REALITY; COMBINATORIAL OPTIMIZATION; ELECTRIC BATTERIES; LEARNING ALGORITHMS; OBJECT DETECTION;

EID: 85056159748     PISSN: 0743166X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INFOCOM.2018.8485905     Document Type: Conference Paper
Times cited : (420)

References (27)
  • 1
    • 84879691323 scopus 로고    scopus 로고
    • Expected user experience of mobile augmented reality services: A user study in the context of shopping centres
    • February
    • Thomas Olsson et al. Expected user experience of mobile augmented reality services: A user study in the context of shopping centres. Personal Ubiquitous Comput., 17 (2): 287-304, February 2013.
    • (2013) Personal Ubiquitous Comput. , vol.17 , Issue.2 , pp. 287-304
    • Olsson, T.1
  • 3
    • 84904608165 scopus 로고    scopus 로고
    • Deepface: Closing the gap to human-level performance in face verification
    • Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato, and Lior Wolf. Deepface: Closing the gap to human-level performance in face verification. In IEEE CVPR, 2014.
    • (2014) IEEE CVPR
    • Taigman, Y.1    Yang, M.2    Ranzato, M.3    Wolf, L.4
  • 6
    • 84979781377 scopus 로고    scopus 로고
    • Deepsense: A GPU-based deep convolutional neural network framework on commodity mobile devices
    • Loc Nguyen Huynh, Rajesh Krishna Balan, and Youngki Lee. Deepsense: A gpu-based deep convolutional neural network framework on commodity mobile devices. In ACM WearSys, 2016.
    • (2016) ACM WearSys
    • Nguyen Huynh, L.1    Krishna Balan, R.2    Lee, Y.3
  • 7
    • 85026268407 scopus 로고    scopus 로고
    • Deepmon: Mobile GPU-based deep learning framework for continuous vision applications
    • Loc N. Huynh, Youngki Lee, and Rajesh Krishna Balan. Deepmon: Mobile gpu-based deep learning framework for continuous vision applications. ACM MobiSys, 2017.
    • (2017) ACM MobiSys
    • Huynh, L.N.1    Lee, Y.2    Krishna Balan, R.3
  • 8
    • 85030149369 scopus 로고    scopus 로고
    • Mcdnn: An approximationbased execution framework for deep stream processing under resource constraints
    • Seungyeop Han, Haichen Shen, Matthai Philipose, Sharad Agarwal, Alec Wolman, and Arvind Krishnamurthy. Mcdnn: An approximationbased execution framework for deep stream processing under resource constraints. In ACM Mobisys, 2016.
    • (2016) ACM Mobisys
    • Han, S.1    Shen, H.2    Philipose, M.3    Agarwal, S.4    Wolman, A.5    Krishnamurthy, A.6
  • 9
    • 85025681138 scopus 로고    scopus 로고
    • YOLO9000: Better, faster, stronger
    • Joseph Redmon and Ali Farhadi. YOLO9000: better, faster, stronger. IEEE CVPR, 2017.
    • (2017) IEEE CVPR
    • Redmon, J.1    Farhadi, A.2
  • 10
    • 84960980241 scopus 로고    scopus 로고
    • Faster r-cnn: Towards real-time object detection with region proposal networks
    • Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. NIPS, 2015.
    • (2015) NIPS
    • Ren, S.1    He, K.2    Girshick, R.3    Sun, J.4
  • 13
    • 84962319574 scopus 로고    scopus 로고
    • A control-theoretic approach for dynamic adaptive video streaming over http
    • Xiaoqi Yin, Abhishek Jindal, Vyas Sekar, and Bruno Sinopoli. A control-theoretic approach for dynamic adaptive video streaming over http. ACM SIGCOMM, 2015.
    • (2015) ACM SIGCOMM
    • Yin, X.1    Jindal, A.2    Sekar, V.3    Sinopoli, B.4
  • 16
    • 85030165860 scopus 로고    scopus 로고
    • Tensorflow android camera demo. https://github. com/tensorflow/tensorflow/tree/master/tensorflow/examples/android, 2017.
    • (2017) Tensorflow Android Camera Demo
  • 18
    • 85056182741 scopus 로고    scopus 로고
    • libstreaming. https://github. com/fyhertz/libstreaming, 2017.
    • (2017)
  • 19
    • 85056148165 scopus 로고    scopus 로고
    • xiph org video test media
    • xiph. org video test media. https://media. xiph. org/video/derf/, 2017.
    • (2017)
  • 20
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. NIPS, 2012.
    • (2012) NIPS
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 21
  • 23
    • 79961048093 scopus 로고    scopus 로고
    • Odessa: Enabling interactive perception applications on mobile devices
    • Moo-Ryong Ra, Anmol Sheth, Lily Mummert, Padmanabhan Pillai, David Wetherall, and Ramesh Govindan. Odessa: Enabling interactive perception applications on mobile devices. In ACM MobiSys, 2011.
    • (2011) ACM MobiSys
    • Ra, M.1    Sheth, A.2    Mummert, L.3    Pillai, P.4    Wetherall, D.5    Govindan, R.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.