Add to ORKGIn order to accelerate data processing and improve classification accuracy, some classic dimension reduction techniques have been proposed in the past few decades, such as Principal Component Analysi
In this paper we present a face recognition system based on the Scale Invariant Feature Transform (S...
This report presents the concepts of both Principal Component Analysis and Eigenfeature Regularizati...
Faces are highly deformable objects which can easily change their appearance over time. All face are...
In this paper, we conduct a comprehensive study on dimensionality reduction (DR) techniques and disc...
Face image retrieval systems have attained much importance in recent times, due to many real time ap...
In undersampled problems where the number of samples is smaller than the di-mension of data space, i...
In this paper a new approach to face recognition is presented that achieves double dimension reducti...
This paper presents a novel dimensionality reduction algorithm for kernel based classification. In t...
Face recognition has been a very popular research for several years with the increasing demand for a...
In this paper a new approach to face recognition is presented that achieves double dimension reducti...
The aim of this project is to develop a face recognition system based on Scale-Invariant Feature Tra...
In this paper we present a face recognition system based on the Scale Invariant Feature Transform (S...
In undersampled problems where the number of samples is smaller than the dimension of data space, it...
Abstract — Unsupervised or Self-Organized learning algorithms have become very popular for discovery...
With rapid development of image recognition technology and increasing demand for a fast yet robust c...
In this paper we present a face recognition system based on the Scale Invariant Feature Transform (S...
This report presents the concepts of both Principal Component Analysis and Eigenfeature Regularizati...
Faces are highly deformable objects which can easily change their appearance over time. All face are...
In this paper, we conduct a comprehensive study on dimensionality reduction (DR) techniques and disc...
Face image retrieval systems have attained much importance in recent times, due to many real time ap...
In undersampled problems where the number of samples is smaller than the di-mension of data space, i...
In this paper a new approach to face recognition is presented that achieves double dimension reducti...
This paper presents a novel dimensionality reduction algorithm for kernel based classification. In t...
Face recognition has been a very popular research for several years with the increasing demand for a...
In this paper a new approach to face recognition is presented that achieves double dimension reducti...
The aim of this project is to develop a face recognition system based on Scale-Invariant Feature Tra...
In this paper we present a face recognition system based on the Scale Invariant Feature Transform (S...
In undersampled problems where the number of samples is smaller than the dimension of data space, it...
Abstract — Unsupervised or Self-Organized learning algorithms have become very popular for discovery...
With rapid development of image recognition technology and increasing demand for a fast yet robust c...
In this paper we present a face recognition system based on the Scale Invariant Feature Transform (S...
This report presents the concepts of both Principal Component Analysis and Eigenfeature Regularizati...
Faces are highly deformable objects which can easily change their appearance over time. All face are...