In investigation of neurological diseases, accurate measurement of hippocampus is very important for differentiating inter-subject difference and subtle longitudinal change. Although many automatic segmentation methods have been developed, their performance can be limited by the poor image contrast of hippocampus in the MR images, acquired from either 1.5T or 3.0T scanner. Recently, the emergen...

In this paper, we present the system and learning strategies that were applied by the IBM Research team to the plant identification task of LifeCLEF 2014. Plant identification is one of the most popular fine-grained categorization tasks. To ensure high classification accuracy, we have utilised strong visual features together with fusion of robust machine learning techniques. Our proposed system...

With the continuous attempts to develop effective machine learning methods, information fusion approaches play an important role in integrating data from multiple sources and improving these methods' performance. Among different techniques, decision-level has unique advantages fuse decisions of various classifiers getting outcome. In this paper, we propose a method that combines three well-cali...

In the last decades many classification methods and fusers have been developed. Considerable gains have been achieved in the classification performance by fusing and combining different classifiers. We experiment a new method for ship infrared imagery recognition based on the fusion of individual results in order to obtain a more reliable decision [1]. To optimize the results of every class of ...

A biometric system which is based only on a single biometric identifier in making a personal identification is often not able to meet the desired performance requirements. Multimodal biometrics is an emerging field of biometric technology, where more than one biometric trait to improve the combined performance. We introduce a bimodal biometric system which integrates face and fingerprint. This ...

In the past decades most object recognition systems were based on passive approaches. But in the last few years a lot of research was done in the field of active approaches for object recognition. In this context there are several unique problems to be solved. One of them is how to fuse images from several viewpoints. In this paper we present a well-founded approach for the fusion of multiple v...

An appropriate combination of multiple biometric sensors increases the reliability of verification through biometrics. In this paper we propose an effective method of fusion of biometrics based on a dynamic selection of threshold point of fingerprint and iris biometrics towards identifier of an optimal set of rules for fusion. The effectiveness of the method has been established using several b...

This chapter describes a new Speaker Discrimination System (SDS), which is a part of an overall project called Audio Documents Indexing based on a Speaker Discrimination System (ADISDS). Speaker discrimination consists in checking whether two speech segments come from the same speaker or not. This research domain presents an important field in biometry, since the voice remains an important feat...

In this paper a new hierarchical age estimation method based on decision level fusion of global and local features is proposed. The shape and appearance information of human faces which are extracted with active appearance models (AAM) are used as global facial features. The local facial features are the wrinkle features extracted with Gabor filters and skin features extracted with local binary...