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Quintella et al., 2024 - Google Patents

Using Cropped Datasets for training Deep Neural Networks for face recognition

Quintella et al., 2024

Document ID
10398512371375539878
Author
Quintella F
Ganacim F
Hurtado J
Raposo A
Publication year
Publication venue
2024 31st International Conference on Systems, Signals and Image Processing (IWSSIP)

External Links

Snippet

Face recognition is a fundamental problem in numerous real-world applications, and it can be tackled using classification deep learning models. This kind of solution requires extensive datasets to represent the target subjects, where maintaining their privacy is …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
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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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    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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    • G—PHYSICS
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