Afzal et al., 2022 - Google Patents
Discriminative feature abstraction by deep L2 hypersphere embedding for 3D mesh CNNsAfzal 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 …
- 238000010606 normalization 0 abstract description 45
Classifications
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- 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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- G06K9/6279—Classification techniques relating to the number of classes
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- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
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- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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