Latest Publications

Kernel Orthogonal Nonnegative Matrix Factorization: Application to Multispectral Document Image Decomposition

By |May 9th, 2022|Categories: 2021, Publications|Tags: , |

As a nonlinear extension of the standard nonnegative matrix factorization (NMF), kernel-based variants have demonstrated to be more effective for discovering meaningful latent features from raw data. However, many existing kernel methods allow only obtaining the basis matrix in the […]

ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)|

Blind Decomposition of Multispectral Document Images Using Orthogonal Nonnegative Matrix Factorization

By |May 9th, 2022|Categories: 2021, Publications|Tags: , |

This paper addresses the challenge of Multispectral (MS) document image segmentation, which is an essential step for subsequent document image analysis. Most previous studies have focused only on binary (text/non-text) separation. They also rely on handcrafted features and techniques dedicated […]

Forgery Detection in Hyperspectral Document Images using Graph Orthogonal Nonnegative Matrix Factorization

By |May 9th, 2022|Categories: 2020, Publications|Tags: , |

The analysis of inks plays a crucial role in the examination process of questioned documents. To address this issue, we propose a new approach for ink mismatch detection in Hyperspectral […]

IEEE/CVF conference on computer vision and pattern recognition workshops|

Feature learning for footnote-based document image classification

By |May 8th, 2022|Categories: 2017, Publications|Tags: , , , , , , |

Classifying document images is a challenging problem that is confronted by many obstacles; specifically, the pivotal need of hand-designed features and the scarcity of labeled data. In this paper, a new approach for classifying document […]

International Conference Image Analysis and Recognition|

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