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A hybrid HMM/SVM classifier for motion recognition using μIMU data
2007 Edition, December 1, 2007 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This paper describes a novel approach for human motion recognition via motion features extracted from sensor data. The classification process consists of two phases. The first one is a preprocessing of raw signals. Median Filter is used to...

Independent-speaker isolated word speech recognition based on mean-shift framing using hybrid HMM/SVM classifier
2010 Edition, May 1, 2010 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This paper studies an independent-speaker isolated word speech recognition based on mean-shift framing using hybrid HMM/SVM classifier. The proposed framework includes two main units: preprocessing unit, and classification unit. The first unit tries to...

Human gait classification using combined HMM & SVM hybrid classifier
2015 Edition, January 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

The paper describes the work on human gait recognition using Hidden Markov Model (HMM), Support Vector Machine (SVM) and Hybridized classifiers (developed using both HMM and SVM). Human gait data obtained from CASIA gait database were...

Local Orthogonal Discriminate Bases to Hybrid SVM/Self-adaptive HMM Classifier for Discrete Word Speech Recognition
2006 Edition, August 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This research addresses speech recognition with discrete words and speaker independent by using hybrid support vector machine/self-adaptive hidden Markov model (SVM/self-adaptive HMM) classifier. Our proposed method includes two main units: preprocessing...

Hybrid EMG classifier based on HMM and SVM for hand gesture recognition in prosthetics
2015 Edition, March 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Pattern recognition and classification algorithms are widely studied in natural gesture interfaces for upper limb prostheses. Robustness and accuracy of control systems are key challenge in such applications. To improve the classification performance, the conventional approach builds...

Real-time Recognition of Multi-category Human Motion Using μIMU Data
2007 Edition, August 1, 2007 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This paper describes a novel approach for human motion recognition via motion feature vectors collected from a micro Inertial Measurement Unit (μlMU), which measures angular rates and accelerations of the three different directions in the workspace based on...

Signal Classification Based on Cyclostationary Spectral Analysis and HMM/SVM in Cognitive Radio
2009 Edition, Volume 3, April 1, 2009 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Distinction of the type of modulated signals is very important in cognitive radio system. In this paper, a novel approach to signal classification is proposed for cognitive radio. Combining the spectral cyclostationary features, embed SVM into the framework of HMM to...

Gesture recognition using hybrid generative-discriminative approach with Fisher Vector
2015 Edition, May 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Gesture recognition is used for many practical applications such as human-robot interaction, medical rehabilitation and sign language. In this paper, we apply a hybrid generative-discriminative approach by using the Fisher Vector to improve the...

A Speech Recognition System Based on a Hybrid HMM/SVM Architecture
2006 Edition, Volume 2, January 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Most of the speech recognition systems are all based on the technology of HMM because that HMM is a valid probability tool for modeling and recognizing time-series signal and can provide a better statistical architecture. But the weakness such as the poor...

Handwritten Assamese numeral recognizer using HMM & SVM classifiers
2013 Edition, February 1, 2013 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This work describes the development of Assamese online numeral recognition system using Hidden Markov Models (HMM) and Support Vector Machines (SVM). Preprocessed (x, y) coordinates and their first and second derivatives at each point are used as features...

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