Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

NUCLEAR TECHNIQUES, Volume. 48, Issue 5, 050004(2025)

Research on real-time online image compression of HEPS-BPIX4 DAQ based on the object detection algorithm

Pengfei XIAO1,2, Xiaolu JI2, Xuanzheng YANG2, and Ping CAO1、*
Author Affiliations
  • 1University of Science and Technology of China, Hefei 230026, China
  • 2Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (19)
    Equations (0)
    References (23)
    Tools
    Paper Information
    Topics
    References(23)

    [1] Jiang X M, Wang J Q, Qin Q et al. The Chinese high-energy photon source and its R&D project[J]. Synchrotron Radiation News, 27, 27-31(2014).

    [2] Li H X, Zhang J, Ding Y et al. A dual module parallel readout system based on 10 Gb TCP/IP transmission for HEPS-BPIX detector[J]. IEEE Transactions on Nuclear Science, 68, 2624-2629(2021).

    [3] Yang X Z, Ji X L, Zhu K J et al. Design and implementation of DAQ system for HEPS-BPIX4[J]. IEEE Transactions on Nuclear Science, 72, 372-379(2025).

    [4] CAO Jianfeng, LI Liangang, WANG Junjing. A study on hybrid compression methods for multichannel spectrometer spectral data[J]. Nuclear Electronics & Detection Technology, 42, 664-667(2022).

    [5] LOU Shiyu, ZHAO Shujun, JIANG Xiaoshan. Study of Huffman code in data processing of JUNO electronic data[J]. Nuclear Electronics & Detection Technology, 37, 231-236(2017).

    [6] GAO Zepeng, LI Qingfeng. Studies on several problems in nuclear physics by using machine learning[J]. Nuclear Techniques, 46, 080009(2023).

    [7] LI Fupeng, PANG Longgang, WANG Xinnian. Application of machine learning to the study of QCD transition in heavy ion collisions[J]. Nuclear Techniques, 46, 040014(2023).

    [8] Sujitha B, Parvathy V S, Lydia E L et al. Optimal deep learning based image compression technique for data transmission on industrial Internet of Things applications[J]. Transactions on Emerging Telecommunications Technologies, 32, e3976(2021).

    [9] CHEN Yutong. Research on image compression algorithms based on machine learning[J]. Computer Programming Skills & Maintenance, 2023, 156-158(2023).

    [10] Yasin H M, Abdulazeez A M. Image compression based on deep learning: a review[J]. Asian Journal of Research in Computer Science, 8, 62-76(2021).

    [11] Girshick R, Donahue J, Darrell T et al. Rich feature hierarchies for accurate object detection and semantic segmentation[EB/OL], 1311.2524(2013). https://arxiv.org/abs/1311.2524v5

    [12] Girshick R. Fast R-CNN[C](2015).

    [13] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[EB/OL], 1506.01497(2015). https://arxiv.org/abs/1506.01497v3

    [14] Redmon J. You only look once: Unified, real-time object detection[C](2016).

    [15] Vaswani A. Attention is all you need[C](2017).

    [16] Zhu X Z, Su W J, Lu L W et al. Deformable DETR: deformable transformers for end-to-end object detection[EB/OL], 2010.04159(2020). https://arxiv.org/abs/2010.04159v4

    [17] Hussain M. YOLO-v1 to YOLO-v8, the rise of YOLO and its complementary nature toward digital manufacturing and industrial defect detection[J]. Machines, 11, 677(2023).

    [18] Wang A, Chen H, Liu L H et al. YOLOv10: real-time end-to-end object detection[EB/OL], 2405.14458(2024). https://arxiv.org/abs/2405.14458v2

    [19] Ketkar N, Moolayil J, Ketkar N et al. Introduction to PyTorch[M]. Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch, 27-91(2021).

    [20] Shridhar A, Tomson P, Innes M. Interoperating deep learning models with ONNX.jl[C], 1, 59(2020).

    [21] Kim J H, Lee D E, Choi S B et al. ONNX-based runtime performance analysis: YOLO and ResNet[J]. The Journal of Bigdata, 9, 89-100(2024).

    [22] Gopiktrishna P B, Marion Lincy G R, Rishekeeshan Abhishek et al. Accelerating native inference model performance in edge devices using TensorRT[C](2024).

    [23] Maulidina A P, Wijaya R A, Mazel K et al. Comparative study of data compression algorithms: zstandard, zlib & LZ4[C], 394-406(2024).

    Tools

    Get Citation

    Copy Citation Text

    Pengfei XIAO, Xiaolu JI, Xuanzheng YANG, Ping CAO. Research on real-time online image compression of HEPS-BPIX4 DAQ based on the object detection algorithm[J]. NUCLEAR TECHNIQUES, 2025, 48(5): 050004

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: Special Topics on Applications of Machine Learning in Nuclear Physics and Nuclear Data

    Received: Dec. 28, 2024

    Accepted: --

    Published Online: Jun. 26, 2025

    The Author Email: Ping CAO (曹平)

    DOI:10.11889/j.0253-3219.2025.hjs.48.240542

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology