1 |
阴艳超, 梁珉清, 张万达, 等. 基于云边协同的智能数控车间自调控系统研究与实现[J/OL]. 计算机集成制造系统: 1-18 (2023-04-10) [2023-10-22]. . YIN Y C, LIANG M Q, ZHANG W D, et al. Research and implementation of intelligent NC workshop self-regulation system based on cloud-edge collaboration[J/OL]. Computer Integrated Manufacturing Systems: 1-18 (2023-04-10) [2023-10-22]. .
|
2 |
KIM S, PARK J, JEONG Y, et al. Intelligent monitoring system with privacy preservation based on edge AI[J]. Micromachines, 2023, 14(9): 1749.
|
3 |
HU L Y, SUN G D, REN Y L. CoEdge: exploiting the edge-cloud collaboration for faster deep learning[J]. IEEE Access, 2020, 8: 100533-100541.
|
4 |
WANG D Y, SUN X B, LIU Y, et al. Research on edge computing and caching resource allocation mechanism for multi-view video[C]//2022 10th International Conference on Intelligent Computing and Wireless Optical Communications. Chongqing, Jun. 10-12, 2022.
|
5 |
LI E, ZHOU Z, CHEN X. Edge intelligence: on-demand deep learning model co-inference with device-edge synergy[C]//Proceedings of the 2018 Workshop on Mobile Edge Communications. Budapest, Aug. 20, 2018.
|
6 |
NIKOUEI S Y, CHEN Y, SONG S J, et al. Real-time human detection as an edge service enabled by a lightweight CNN[C]//2018 IEEE International Conference on Edge Computing. San Francisco, CA, Jul. 2-7, 2018.
|
7 |
YAO S C, ZHAO Y R, ZHANG A, et al. DeepIoT: compressing deep neural network structures for sensing systems with a compressor-critic framework[C]// Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. Delft, Nov. 6-8, 2017.
|
8 |
李华, 赵领娣, 陈雨杰, 等. 多流融合的轻量级图卷积行为识别算法[J]. 计算机科学, 2023, 50(11A): 220800147-6. LI H, ZHAO L D, CHEN Y J, et al. Lightweight graph convolution action recognition algorithm based on multi-stream fusion[J]. Computer Science, 2023, 50(11A): 220800147-6.
|
9 |
辛莉, 赵钦炎, 许茜, 等. 基于计算机视觉的复杂场景车牌识别算法[J]. 制造业自动化, 2021, 43(12): 135-139. XIN L, ZHAO Q Y, XU Q, et al. License plate recognition algorithm in complex scene based on computer vision[J]. Manufacturing Automation, 2021, 43(12): 135-139.
|
10 |
LI Y J, ZHANG S K, WANG Z C, et al. TokenPose: learning keypoint tokens for human pose estimation[C]//2021 IEEE/CVF International Conference on Computer Vision. Montreal, QC, Oct. 10-17, 2021.
|
11 |
LI H, OTA K, DONG M X. Learning IoT in edge: deep learning for the Internet of Things with edge computing[J]. IEEE Network, 2018, 32(1): 96-101.
|
12 |
LIU C, CAO Y, LUO Y, et al. A new deep learning-based food recognition system for dietary assessment on an edge computing service infrastructure[J]. IEEE Transactions on Services Computing, 2018, 11(2): 249-261.
|
13 |
JIANG A H, WONG D L K, CANEL C, et al. Mainstream: dynamic stem-sharing for multi-tenant video processing[C]//Proceedings of the 2018 USENIX Annual Technical Conference. Boston, MA, Jul. 11-13, 2018.
|
14 |
TEERAPITTAYANON S, MCDANEL B, KUNG H T. Distributed deep neural networks over the cloud, the edge and end devices[C]//2017 IEEE 37th International Conference on Distributed Computing Systems. Atlanta, GA, Jun. 5-8, 2017.
|
15 |
MAO J C, CHEN X, NIXON K W, et al. MoDNN: local distributed mobile computing system for deep neural network[C]//Design, Automation & Test in Europe Conference & Exhibition. Lausanne, Mar. 27-31, 2017.
|
16 |
ZHAO Z R, BARIJOUGH K M, GERSTLAUER A. DeepThings: distributed adaptive deep learning inference on resource-constrained IoT edge clusters[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018, 37(11): 2348-2359.
|
17 |
DING C T, ZHOU A, LIU Y X, et al. A cloud-edge collaboration framework for cognitive service[J]. IEEE Transactions on Cloud Computing, 2022, 10(3): 1489-1499.
|
18 |
CHAKRABORTY S, MAZUMDAR K, DE D, et al. RMS: a delay sensitive road monitoring system using edge intelligence[J]. IEEE Sensors Journal, 2023, 23(3): 2643-2650.
|
19 |
HSU C W, HSU Y L, WEI H Y. Energy-efficient edge offloading in heterogeneous industrial IoT networks for factory of future[J]. IEEE Access, 2020, 8: 183035-183050.
|
20 |
BOUKERCHE A, GUAN S C, DE GRANDE R E. Sustainable offloading in mobile cloud computing[J]. ACM Computing Surveys, 2020, 52(1): 1-37.
|
21 |
WANG Z Y, CUI Y, LAI Z Q. A first look at mobile intelligence: architecture, experimentation and challenges[J]. IEEE Network, 2019, 33(4): 120-125.
|
22 |
CAI X Y, ZHOU W G, WU L, et al. Effective active skeleton representation for low latency human action recognition[J]. IEEE Transactions on Multimedia, 2016, 18(2): 141-154.
|
23 |
WU H Y, ALBIERO V, KRISHNAPRIYA K S, et al. Face recognition accuracy across demographics: shining a light into the problem[C]//2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. Vancouver, BC, Jun. 17-24, 2023.
|
24 |
HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, NV, Jun. 27-30, 2016.
|