765 citations · 1.5k across the 62 of their papers we have counts for
13 papers · 1 filter
Roweis Discriminant Analysis: A Generalized Subspace Learning Method
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
We present a new method which generalizes subspace learning based on eigenvalue and generalized eigenvalue problems. This method, Roweis Discriminant Analysis (RDA), is named after…
Quantized Fisher Discriminant Analysis
Benyamin Ghojogh, Ali Saheb Pasand, Fakhri Karray +1
This paper proposes a new subspace learning method, named Quantized Fisher Discriminant Analysis (QFDA), which makes use of both machine learning and information theory. There is a…
Locally Linear Image Structural Embedding for Image Structure Manifold Learning
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Most of existing manifold learning methods rely on Mean Squared Error (MSE) or norm. However, for the problem of image quality assessment, these are not promising measure.…
Principal Component Analysis Using Structural Similarity Index for Images
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Despite the advances of deep learning in specific tasks using images, the principled assessment of image fidelity and similarity is still a critical ability to develop. As it has b…
Fisher and Kernel Fisher Discriminant Analysis: Tutorial
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
This is a detailed tutorial paper which explains the Fisher discriminant Analysis (FDA) and kernel FDA. We start with projection and reconstruction. Then, one- and multi-dimensiona…
Unsupervised and Supervised Principal Component Analysis: Tutorial
Benyamin Ghojogh, Mark Crowley
This is a detailed tutorial paper which explains the Principal Component Analysis (PCA), Supervised PCA (SPCA), kernel PCA, and kernel SPCA. We start with projection, PCA with eige…