Abstract—When the number of labeled training samples is very small, the sample information we can use would be very little. Because of this, the recognition rates of some traditional image recognition methods are not satisfactory. In order to use some related information that always exist in other databases, which is helpful to feature extraction and can improve the recognition rates, we apply multi-task learning to feature extraction of images. Our researches are based on transferring the projection transformation. Our experiments results on the public AR, FERET and CAS-PEAL databases demonstrate that the proposed approaches are more effective than the general related feature extraction methods in classification performance. Keywords-multi...
Abstract — Dictionary learning algorithms have been success-fully used for both reconstructive and d...
In this paper we study the reliability of the methods of Face Recognition on the ground of the preci...
Facial feature extraction consists in localizing the most characteristic face components (eyes, nose...
In this paper, we propose a new supervised linear feature extraction technique for multiclass classi...
Multi-task learning aims at improving the generalization performance of a learning task with the hel...
This paper presents a new joint feature learning (JFL) approach to automatically learn feature repre...
This project presents the facial feature extraction system and face recognition system. The test ima...
© 2015 IEEE. The features used in many image analysis-based applications are frequently of very high...
International audienceWe propose a novel Coupled Projection multi-task Metric Learning (CP-mtML) met...
Among various feature extraction algorithms, those based on genetic algorithms are promising owing t...
Feature extraction is a procedure aimed at selecting and transforming a data set in order to increas...
Multitask Learning is a novel machine learning approach that learns each problem better by also lear...
This paper proposes a step toward obtaining general models of knowledge for facial analysis, by addr...
This study investigates a new method of feature extraction for classification prob-lems. The method ...
© 2015 Elsevier B.V. Regarded as two independent tasks, both face identification and facial expressi...
Abstract — Dictionary learning algorithms have been success-fully used for both reconstructive and d...
In this paper we study the reliability of the methods of Face Recognition on the ground of the preci...
Facial feature extraction consists in localizing the most characteristic face components (eyes, nose...
In this paper, we propose a new supervised linear feature extraction technique for multiclass classi...
Multi-task learning aims at improving the generalization performance of a learning task with the hel...
This paper presents a new joint feature learning (JFL) approach to automatically learn feature repre...
This project presents the facial feature extraction system and face recognition system. The test ima...
© 2015 IEEE. The features used in many image analysis-based applications are frequently of very high...
International audienceWe propose a novel Coupled Projection multi-task Metric Learning (CP-mtML) met...
Among various feature extraction algorithms, those based on genetic algorithms are promising owing t...
Feature extraction is a procedure aimed at selecting and transforming a data set in order to increas...
Multitask Learning is a novel machine learning approach that learns each problem better by also lear...
This paper proposes a step toward obtaining general models of knowledge for facial analysis, by addr...
This study investigates a new method of feature extraction for classification prob-lems. The method ...
© 2015 Elsevier B.V. Regarded as two independent tasks, both face identification and facial expressi...
Abstract — Dictionary learning algorithms have been success-fully used for both reconstructive and d...
In this paper we study the reliability of the methods of Face Recognition on the ground of the preci...
Facial feature extraction consists in localizing the most characteristic face components (eyes, nose...