Results 221 to 230 of about 282,565 (268)

Feature Fusion Techniques

2015
Researcher introduced biometric system to improve the security because nowadays, the world is becoming more insecure. The term Biometrics is derived from the Greek composite words bio and metric. Bio means life and metric means to measure. Biometrics basically is a measure and analysis of human physiological and behavioral characteristics to identify ...
Koteswara Rao Anne, Swarna Kuchibhotla, Hima Deepthi Vankayalapati   +2 more
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Intact and deficient feature fusion in schizophrenia

European Archives of Psychiatry and Clinical Neuroscience, 2005
In patients with schizophrenia, early as well as late stages of information processing can be deficient. Therefore, it is important to determine the earliest occurrences of aberrant processing since deficits on these stages may cause abnormal processing on later, e. g. cognitive, levels.
Brand, Andreas, Kopmann, Sabine, Marbach, Sonja, Heinze, Martin, Herzog, Michael H.   +4 more
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Multi-Exposure Fusion with CNN Features

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
Multi-exposure fusion (MEF) is a widely used approach to high dynamic range imaging. The selection of features for fusion weight calculation is important to the performance of MEF. In this paper, we investigate the effectiveness of convolutional neural network (CNN) features for MEF.
Hui Li 0029, Lei Zhang 0006
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A method towards biometric feature fusion

International Journal of Biometrics, 2009
For multimodal biometric person recognition, information fusion can be classified into several levels: rank, decision, sensor, feature and match-score levels. In this paper, a novel method is proposed to fuse information from two or more biometric sources at feature fusion level.
Lin Huang 0001, Hanqi Zhuang, Salvatore D. Morgera   +2 more
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Feature Comparison and Feature Fusion for Traditional Dances Recognition

2013
Traditional dances constitute a significant part of the cultural heritage around the world. The great variety of traditional dances along with the complexity of some dances increases the difficulty of identifying such dances, thus making the traditional dance recognition a challenging subset within the general field of activity recognition.
Ioannis Kapsouras, Stylianos Karanikolos, Nikolaos Nikolaidis 0001, Anastasios Tefas   +3 more
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Multiple feature fusion for face recognition

2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), 2013
Recent studies show face recognition (FR) with additional features achieves better performance than that with single one. Different features can represent different characteristics of human faces, and utilizing different features effectively will have positive effect on FR.
Shu Kong, Xikui Wang, Donghui Wang, Fei Wu 0001   +3 more
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Linear dependency modeling for feature fusion

2011 International Conference on Computer Vision, 2011
This paper addresses the independent assumption issue in fusion process. In the last decade, dependency modeling techniques were developed under a specific distribution of classifiers. This paper proposes a new framework to model the dependency between features without any assumption on feature/classifier distribution.
Andy Jinhua Ma, Pong Chi Yuen
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A Fuzzy Vault Scheme for Feature Fusion

2011
Widespread application of biometric authentication brings about new problem of privacy. Biometric template protection is becoming a hot research. Efficient feature fusion is deemed to have good performance possibly. In this paper we proposed a fuzzy vault scheme for feature fusion. In our scheme, two facial features Multi-Block Local Binary Pattern (MB-
Lifang Wu, Peng Xiao, Siyuan Jiang, Xin Yang 0001   +3 more
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Hierarchical Feature Fusion for Visual Tracking

2007 IEEE International Conference on Image Processing, 2007
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from cluttered scenes. The tracked object is described by several models of different complexity, which are probabilistically linked together.
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavros J. Perantonis, Sergios Theodoridis   +3 more
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Multi-feature fusion deep networks

Neurocomputing, 2016
In this paper, we propose a novel deep networks, multi-feature fusion deep networks (MFFDN), based on denoising autoencoder. MFFDN significantly reduces the classification error while giving the interpretability of the hidden-layer feature representation in learning process.
Gang Ma 0001, Xi Yang, Bo Zhang 0022, Zhongzhi Shi   +3 more
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