IES87348Y1 - Vehicle object detection method based on deep learning - Google Patents

Vehicle object detection method based on deep learning

Info

Publication number
IES87348Y1
IES87348Y1 IE20210204U IE20210204U IES87348Y1 IE S87348 Y1 IES87348 Y1 IE S87348Y1 IE 20210204 U IE20210204 U IE 20210204U IE 20210204 U IE20210204 U IE 20210204U IE S87348 Y1 IES87348 Y1 IE S87348Y1
Authority
IE
Ireland
Prior art keywords
object detection
deep learning
detection method
method based
images
Prior art date
Application number
IE20210204U
Other versions
IE20210204U1 (en
Inventor
Zhu Zhongjie
Liu Tingna
Bai Yongqiang
Wang Yu'er
Liao Guanglong
Zheng Wei
Original Assignee
Univ Zhejiang Wanli
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Univ Zhejiang Wanli filed Critical Univ Zhejiang Wanli
Publication of IE20210204U1 publication Critical patent/IE20210204U1/en
Publication of IES87348Y1 publication Critical patent/IES87348Y1/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computational Linguistics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Evolutionary Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Image Analysis (AREA)
  • Traffic Control Systems (AREA)
  • Image Processing (AREA)

Abstract

Provided is a vehicle object detection method based on deep learning. The method comprises the steps: S1, acquiring road surface images within a preset time by an image acquisition apparatus; S2, pre-processing the acquired road surface images; S3, detecting vehicle objects in the pre-processed vehicle images by a trained preset You Only Look Once (YOLO) network model; and S4, labeling vehicles detected in the images according to classification.
IE20210204U 2021-04-30 2021-12-03 Vehicle object detection method based on deep learning IES87348Y1 (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110478842.8A CN113392852B (en) 2021-04-30 2021-04-30 Vehicle detection method and system based on deep learning

Publications (2)

Publication Number Publication Date
IE20210204U1 IE20210204U1 (en) 2022-12-07
IES87348Y1 true IES87348Y1 (en) 2022-12-21

Family

ID=77617933

Family Applications (1)

Application Number Title Priority Date Filing Date
IE20210204U IES87348Y1 (en) 2021-04-30 2021-12-03 Vehicle object detection method based on deep learning

Country Status (2)

Country Link
CN (1) CN113392852B (en)
IE (1) IES87348Y1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116755081A (en) * 2023-05-25 2023-09-15 东风柳州汽车有限公司 Vision and radar fusion target detection technology

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110472467A (en) * 2019-04-08 2019-11-19 江西理工大学 The detection method for transport hub critical object based on YOLO v3
CN110175658A (en) * 2019-06-26 2019-08-27 浙江大学 A kind of distress in concrete recognition methods based on YOLOv3 deep learning
AU2019101142A4 (en) * 2019-09-30 2019-10-31 Dong, Qirui MR A pedestrian detection method with lightweight backbone based on yolov3 network
AU2020100705A4 (en) * 2020-05-05 2020-06-18 Chang, Jiaying Miss A helmet detection method with lightweight backbone based on yolov3 network
CN112232214A (en) * 2020-10-16 2021-01-15 天津大学 Real-time target detection method based on depth feature fusion and attention mechanism
CN112529090B (en) * 2020-12-18 2023-01-17 天津大学 Small target detection method based on improved YOLOv3
CN115456938A (en) * 2022-07-20 2022-12-09 河南科技大学 Metal part crack detection method based on deep learning and ultrasonic infrared image

Also Published As

Publication number Publication date
IE20210204U1 (en) 2022-12-07
CN113392852B (en) 2024-02-13
CN113392852A (en) 2021-09-14

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