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Afzal et al., 2022 - Google Patents

Discriminative feature abstraction by deep L2 hypersphere embedding for 3D mesh CNNs

Afzal et al., 2022

Document ID
5760713861284068706
Author
Afzal M
Adam J
Afzal H
Zang Y
Bello S
Wang C
Li J
Publication year
Publication venue
Information Sciences

External Links

Snippet

Feature normalization has been a crucial step in convolutional neural networks (CNNs) in the past few years. Discriminative feature abstraction is indispensable for boosting the overall performance of learning models. For 3D data, in both point cloud and mesh models …
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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    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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    • G—PHYSICS
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    • G06F17/50—Computer-aided design
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