A new ranking method for principal components analysis and its application to face image analysis
By Carlos Eduardo Thomaz, Gilson Antonio Giraldi. Image and Vision Computing, 2010
576 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/8b56e33f33e582f3e473dba573a16b598ed9bcdc
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In Analytical Chemistry
In Computer Vision and Pattern Recognition
Citations in the corpus
- Accurate and Robust Neural Networks for Security Related Applications Exampled by Face Morphing Attacks (2018, unknown): “Database BU-4DFE[20] CFD[21] FEI[22] FERET[23] PUT[24]”
- Two-stage Image Classification Supervised by a Single Teacher Single Student Model (2019, methodology): “(c) MUCT, (d) FEI, (e) YouTubeFace.”
- The Chicago face database: A free stimulus set of faces and norming data (2015, unknown): “Like KDEF, some other databases use actors (e.g., Tottenham et al., 2009), but the majority employ lay volunteers (e.g., Belhumeur, Hespanha, & Kriegman, 1997; Minear & Park, 2004; Rhodes, Proffitt, Grady, & Sumich, 1998; Thomaz & Giraldi, 2010).”
- APDrawingGAN: Generating Artistic Portrait Drawings From Face Photos With Hierarchical GANs (2019, methodology): “We collect 6,655 frontal face photos taken from ten face datasets [37, 21, 6, 25, 24, 7, 35, 34, 4, 36].”