How to Boost Deep Neural Networks for Computer Vision

被引:0
作者
Ha, Soonhoi [1 ]
机构
[1] Seoul Natl Univ, Dept Comp Sci & Engn, Seoul, South Korea
来源
2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC | 2023年
关键词
model compression; pruning; quantization; parallelization; neural network search; methodology;
D O I
10.1109/DAC56929.2023.10247892
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As the range of neural network applications has exploded, various model compression techniques have been developed to increase the accuracy of neural networks under the resource constraints given by the hardware platform and the performance constraints required by users. In this perspective paper, the current status and future prospects of individual techniques are briefly summarized. And it presents the importance of understanding the characteristics of the hardware platform and the systematic methodology of applying these techniques harmoniously.
引用
收藏
页数:2
相关论文
共 8 条
  • [1] Neural Architecture Search Survey: A Hardware Perspective
    Chitty-Venkata, Krishna Teja
    Somani, Arun K.
    [J]. ACM COMPUTING SURVEYS, 2023, 55 (04)
  • [2] A comprehensive survey on model compression and acceleration
    Choudhary, Tejalal
    Mishra, Vipul
    Goswami, Anurag
    Sarangapani, Jagannathan
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2020, 53 (07) : 5113 - 5155
  • [3] Five-repetition sit-to-Stand test among patients post-stroke and healthy-matched controls: the use of different chair types and number of trials
    Franco, Juliane
    Quintino, Ludmylla Ferreira
    Faria, Christina D. C. M.
    [J]. PHYSIOTHERAPY THEORY AND PRACTICE, 2021, 37 (12) : 1419 - 1428
  • [4] Gholami A., 2022, LOW POWER COMPUTER V
  • [5] TensorRT-Based Framework and Optimization Methodology for Deep Learning Inference on Jetson Boards
    Jeong, Eunjin
    Kim, Jangryul
    Ha, Soonhoi
    [J]. ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2022, 21 (05)
  • [6] Kang D, 2018, DES AUT TEST EUROPE, P715, DOI 10.23919/DATE.2018.8342102
  • [7] Li Y., 2022, C NEUR INF PESS SYST
  • [8] Efficient Transformers: A Survey
    Tay, Yi
    Dehghani, Mostafa
    Bahri, Dara
    Metzler, Donald
    [J]. ACM COMPUTING SURVEYS, 2023, 55 (06)