GB202217424D0 - Method of crowd density estimation based on multi-scale feature fusion of residual network - Google Patents

Method of crowd density estimation based on multi-scale feature fusion of residual network

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Publication number
GB202217424D0
GB202217424D0 GBGB2217424.7A GB202217424A GB202217424D0 GB 202217424 D0 GB202217424 D0 GB 202217424D0 GB 202217424 A GB202217424 A GB 202217424A GB 202217424 D0 GB202217424 D0 GB 202217424D0
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United Kingdom
Prior art keywords
estimation based
feature fusion
density estimation
scale feature
crowd density
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Pending
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GBGB2217424.7A
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GB2614806A (en
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Aeronautic Polytechnic
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Aeronautic Polytechnic
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Application filed by Aeronautic Polytechnic filed Critical Aeronautic Polytechnic
Publication of GB202217424D0 publication Critical patent/GB202217424D0/en
Publication of GB2614806A publication Critical patent/GB2614806A/en
Pending legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/253—Fusion techniques of extracted features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
    • 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
    • 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
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions
    • 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
    • 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
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/806—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of extracted features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Image Analysis (AREA)
GB2217424.7A 2021-11-22 2022-11-22 Method of crowd density estimation based on multi-scale feature fusion of residual network Pending GB2614806A (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111384302.XA CN113807334B (en) 2021-11-22 2021-11-22 Residual error network-based multi-scale feature fusion crowd density estimation method

Publications (2)

Publication Number Publication Date
GB202217424D0 true GB202217424D0 (en) 2023-01-04
GB2614806A GB2614806A (en) 2023-07-19

Family

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GB2217424.7A Pending GB2614806A (en) 2021-11-22 2022-11-22 Method of crowd density estimation based on multi-scale feature fusion of residual network

Country Status (2)

Country Link
CN (1) CN113807334B (en)
GB (1) GB2614806A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116883360A (en) * 2023-07-11 2023-10-13 大连海洋大学 Multi-scale double-channel-based fish shoal counting method
CN116944818A (en) * 2023-06-21 2023-10-27 台州必拓汽车配件股份有限公司 Intelligent processing method and system for new energy automobile rotating shaft
CN117739289A (en) * 2024-02-20 2024-03-22 齐鲁工业大学(山东省科学院) Leakage detection method and system based on sound-image fusion

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* Cited by examiner, † Cited by third party
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CN114926420B (en) * 2022-05-10 2023-05-30 电子科技大学 Target crusty pancake identification and counting method based on cross-level feature enhancement

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JP2009198819A (en) * 2008-02-21 2009-09-03 Canon Inc Image forming apparatus and method for estimating toner consumption
CN106778502B (en) * 2016-11-21 2020-09-22 华南理工大学 Crowd counting method based on deep residual error network
CN109241895B (en) * 2018-08-28 2021-06-04 北京航空航天大学 Dense crowd counting method and device
CN109460855A (en) * 2018-09-29 2019-03-12 中山大学 A kind of throughput of crowded groups prediction model and method based on focus mechanism
CN110020606B (en) * 2019-03-13 2021-03-30 北京工业大学 Crowd density estimation method based on multi-scale convolutional neural network
US10970837B2 (en) * 2019-03-18 2021-04-06 Siemens Healthcare Gmbh Automated uncertainty estimation of lesion segmentation
CN110705340B (en) * 2019-08-12 2023-12-26 广东石油化工学院 Crowd counting method based on attention neural network field
CN111681236B (en) * 2020-06-12 2022-05-17 成都数之联科技股份有限公司 Target density estimation method with attention mechanism
CN112101164A (en) * 2020-09-06 2020-12-18 西北工业大学 Lightweight crowd counting method based on full convolution network
CN112861718A (en) * 2021-02-08 2021-05-28 暨南大学 Lightweight feature fusion crowd counting method and system
CN112597985B (en) * 2021-03-04 2021-07-02 成都西交智汇大数据科技有限公司 Crowd counting method based on multi-scale feature fusion
CN113139489B (en) * 2021-04-30 2023-09-05 广州大学 Crowd counting method and system based on background extraction and multi-scale fusion network

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116944818A (en) * 2023-06-21 2023-10-27 台州必拓汽车配件股份有限公司 Intelligent processing method and system for new energy automobile rotating shaft
CN116944818B (en) * 2023-06-21 2024-05-24 台州必拓汽车配件股份有限公司 Intelligent processing method and system for new energy automobile rotating shaft
CN116883360A (en) * 2023-07-11 2023-10-13 大连海洋大学 Multi-scale double-channel-based fish shoal counting method
CN116883360B (en) * 2023-07-11 2024-01-26 大连海洋大学 Multi-scale double-channel-based fish shoal counting method
CN117739289A (en) * 2024-02-20 2024-03-22 齐鲁工业大学(山东省科学院) Leakage detection method and system based on sound-image fusion
CN117739289B (en) * 2024-02-20 2024-04-26 齐鲁工业大学(山东省科学院) Leakage detection method and system based on sound-image fusion

Also Published As

Publication number Publication date
CN113807334A (en) 2021-12-17
CN113807334B (en) 2022-02-18
GB2614806A (en) 2023-07-19

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