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Gao et al., 2021 - Google Patents

A novel image-based convolutional neural network approach for traffic congestion estimation

Gao et al., 2021

Document ID
911547685655951231
Author
Gao Y
Li J
Xu Z
Liu Z
Zhao X
Chen J
Publication year
Publication venue
Expert Systems with Applications

External Links

Snippet

Traditional image-based traffic congestion estimation methods generally include two steps, which first extract the vehicles from the surveillance images, then calculate the congestion index using the vehicle counts. When working with vast amount of video frames, these …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
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    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/6288—Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion
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    • G06—COMPUTING; CALCULATING; COUNTING
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    • G—PHYSICS
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