Chen et al., 2022 - Google Patents

Dual-bottleneck feature pyramid network for multiscale object detection

Chen et al., 2022

Document ID
4140035826895141020
Author
Chen S
Ma W
Zhang L
Publication year
Publication venue
Journal of Electronic Imaging

External Links

Snippet

Multiscale object detection is a challenging task due to the multiscale and multiclassification nature of different objects. Convolutional neural networks are commonly used to extract the features. However, continuous downsampling operations and spatial position quantization …
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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
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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    • G06—COMPUTING; CALCULATING; COUNTING
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