Recent applications and developments based on support vector machines (SVMs) have shown that using multiple kernels instead of a single one can enhance classifier performance. However, there are few reports on performance of the kernel‐based Fisher discriminant analysis (kernel‐based FDA) method with multiple kernels. This paper proposes a multiple kernel construction ...

Because of its higher reliability, wider applicability and stronger security, multimodal biometrics has become a polar research direction of biometric recognition and attracts more and more research groups focusing on this area. Along with other fusion level of multimodal biometrics, feature level can reduce the redundant information to avoid calculation consumption, and simultaneously acquire ...

Human re-identification (re-id) in surveillance videos has been widely studied over the past few years. The research effort was mainly focused on building appearance models [1, 3] and learning a suitable metric to determine whether or not an image pair belongs to the same person[5, 8]. In terms of the available number of images per person in each camera view, the re-id problem can be categorize...

To date, most facial expression analysis have been based on posed image databases and is carried out without being able to protect the identity of the subjects whose expressions are being recognised. In this paper, we propose and implement a system for classifying facial expressions of images in the encrypted domain based on a Paillier cryptosystem implementation of Fisher Linear Discriminant A...

Fisher proposed a linear discriminant function (Fisher’s LDF). From 1971, we analysed electrocardiogram (ECG) data in order to develop the diagnostic logic between normal and abnormal symptoms by Fisher’s LDF and a quadratic discriminant function (QDF). Our four years research was inferior to the decision tree logic developed by the medical doctor. After this experience, we discriminated many d...

Unlike many other investigations on this topic, the present one considers the non-linear single-layer perceptron (SLP) as a process in which the weights of the perceptron are increasing, and the cost function of the sum of squares is changing gradually. During the backpropagation training, the decision boundary of of SLP becomes identical or close to that of seven statistical classifiers: (1) t...

To improve the class separability of Fisher linear discriminant analysis (FDA) for large category problems, we investigate the weighted Fisher criterion (WFC) by integrating weighting functions for dimensionality reduction. The objective of WFC is to maximize the sum of weighted distances of all class pairs. By setting larger weights for the most confusable classes, WFC can improve the class se...