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  • International Journal Advanced Network Monitoring Controls

 

Article | 16-December-2013

Electrocardiogram for Biometrics by using Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ): Integrating Feature Extraction and Classification

Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classification method. The experiments shown that AMGLVQ can improve the accuracy of classification better

Elly Matul Imah, Wisnu Jatmiko, T. Basaruddin

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 1891–1917

Article | 01-December-2016

HYPERSPECTRAL DATA FEATURE EXTRACTION USING DEEP BELIEF NETWORK

Jiang Xinhua, Xue Heru, Zhang Lina, Zhou Yanqing

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 4, 1991–2009

Article | 01-September-2014

EMPIRICAL MODE DECOMPOSITION AND ROUGH SET ATTRIBUTE REDUCTION FOR ULTRASONIC FLAW SIGNAL CLASSIFICATION

Feature extraction and selection are the most important techniques for ultrasonic flaw signal classification. In this study, empirical mode decomposition (EMD) is first used to obtain the intrinsic mode functions (IMFs) of original ultrasonic signals. Such IMFs and traditional time as well as frequency domain based statistical parameters are extracted as the initial features of flaw signal. After that, spectral clustering method is used for feature value discretization so that rough set

Yu Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 3, 1401–1420

Article | 10-April-2018

Distributed Computing System Based on Microprocessor Cluster for Wearable Devices

equipment. This article discusses the hardware and software design methods in detail, as well as the complete process of the across-node communication module. In order to verify the principle of the design, we created a prototype test machine which consists of an ARM Cortex-M4 core microprocessor and 10 ARM Cortex-M0 core microprocessors through the UART serial interconnection to form a star network and carried out an experimental about the ECG feature extraction operation. Experimental results show

Xin Liu, Zhiqiang Wei

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 27–32

Research Article | 27-December-2017

STUDY OF VISION BASED HAND GESTURE RECOGNITION USING INDIAN SIGN LANGUAGE

as hand plays vital communication mode. Considering earlier reported work, various techniques available for hand tracking, segmentation, feature extraction and classification are listed. Vision based system have challenges over traditional hardware based approach; by efficient use of computer vision and pattern recognition, it is possible to work on such system which will be natural and accepted, in general.

Archana S. Ghotkar, Dr. Gajanan K. Kharate

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 1, 96–115

research-article | 30-November-2019

Indonesian traffic sign detection based on Haar-PHOG features and SVM classification

objects. Moreover, traffic signs might be physically faded and damaged due to vandalism, making it harder to detect their color and shape. Segmentation is used to separate the color of traffic signs from the background, which is then continued with shape search to find candidates based on feature extraction. Researches on shape features mostly use Histogram of Oriented Gradient (HOG) and Pyramid Histogram of Oriented Gradient (PHOG). HOG uses blocks and cells to determine shape features. In order to

Aris Sugiharto, Agus Harjoko, Suharto Suharto

International Journal on Smart Sensing and Intelligent Systems, Volume 13 , ISSUE 1, 1–15

Research Article | 01-September-2017

A REVIEW ON MULTIPLE-FEATURE-BASED ADAPTIVE SPARSE REPRESENTATION (MFASR) AND OTHER CLASSIFICATION TYPES

S. Srinivasan, Dr. K. Rajakumar

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 3, 567–593

Article | 05-September-2013

Smartphone Application for Fault Recognition

1Nishchal K. Verma, Rahul K. Sevakula, Jayesh K. Gupta, Sumanik Singh, Sonal Dixit, Al Salour

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1763–1782

Article | 30-November-2018

A New Method of Improving the Traditional Traffic Identification and Accuracy

=sgn{i=1n[aiKxi,x-sidi§]}, f (x)≠1 or f(x)≠− 1, The x vector does not belong to the support vector or the x vector belongs to the support vector. An initial support vector library trained from known flows. After the known flow rate is trained by the data acquisition module, the feature extraction module, the data preprocessing module, and the training module, a support vector is generated to perform feature analysis, and its characteristic word information is added to the support vector library

Wang Zhongsheng, Gao Jiaqiong

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 3, 53–60

Article | 01-June-2015

ENHANCED IRIS RECOGNITION BASED ON IMAGE MATCH AND HAMMING DISTANCE

Iris recognition and favor because of its high recognition rate, noninvasive and simple algorithm and other advantages, in a variety of biometric identification technology is very prominent. The iris texture feature extraction is the core of the iris recognition algorithm. Fractal geometry theory provides new ideas and methods to express nonlinear image information, the fractal dimension is an important parameter of fractal geometry, is a measure of complexity of irregular change, covering

Gao Xiaoxing, Feng Sumin, Cui Han

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1085–1103

Article | 07-May-2018

Research on the Key Technology of Survey Measurement Image Based on UAV

Ding Li, Chong Jiao

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 2, 99–103

Research Article | 15-February-2020

Wavelet Transform Smoothing Filters for Metal Oxide Gas Sensor Signal Cleaning

This paper reports on a series of experiments to evaluate the methods for feature extraction and denoising the digital signal from thin film zinc oxide-tin dioxide composite gas sensor devices. The aim was to find a method that not only cleaned the signal but also maintained the shape, precision and resolution of the signal. It was found that the Savitzky–Golay smoothing filter method gave the best, smoothed and cleaned, approximation of the sensor response regardless of the thin film

Enobong Bassey, Jacqueline Whalley, Philp Sallis, Krishnamachar Prasad

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–5

Article | 05-September-2013

PREDICTION OF PCCP FAILURE BASED ON HYDROPHNE DETECTING

Prestressed Concrete Cylinder Pipe (PCCP) is a widely used water pipe all over the world. A major cause of PCCP failure is the internal wire break, which will emit acoustic signal. In this paper, a hydrophone-based PCCP real-time monitoring and failure-prediction system was proposed. By applying wavelet energy normalization analysis to signal feature extraction and Support Vector Machine (SVM) to signal recognition, a high prediction accuracy of 98.33% was achieved. The result showed that the

Yuan Zhang, Yibo Li

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1582–1598

Article | 13-July-2020

Research on the Application of Convolutional Neural Networks in the Image Recognition

models. In the following years, CNN have made leaps and bounds in digital image recognition and processing with their powerful feature extraction capabilities. II. OVERVIEW OF CNN CNN, compared to other network models, are better able to adapt their structures to image structures while extracting features and classifying them, with outstanding performance in image processing. In addition, its weight sharing feature educes the training parameters of the network, which makes the network structure

Gao Zhiyu, Liu Bailin, Gu Hongxian, Mu Jing

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 2, 31–38

Research Article | 01-September-2011

BIOLOGICALLY-INSPIRED VISUAL ATTENTION FEATURES FOR A VEHICLE CLASSIFICATION TASK

A.-M. Cretu, P. Payeur

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 3, 402–423

Research Article | 01-September-2017

MACHINE VISION BASED MISSING FASTENER DETECTION IN RAIL TRACK IMAGES USING SVM CLASSIFIER

Missing fastener detection is a critical task due to its similar characteristics with surrounding environments. In this paper, a machine vision based fully automatic detection and classification of missing fastener detection system is proposed using Support Vector Machine (SVM) classifier. This proposed system consists of preprocessing, transformation, feature extraction and classifications. Image resizing is performed as preprocessing step and Gabor transform is used as transformation

R. Manikandan, M. Balasubramanian, S. Palanivel

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 574–589

Research Article | 27-December-2017

INDEX FINGER MOTION RECOGNITION USING SELF-ADVISE SUPPORT VECTOR MACHINE

Because of the functionality of an index finger, the disability of its motion in the modern age can decrease the person’s quality of life. As a part of rehabilitation therapy, the recognition of the index finger motion for rehabilitation purposes should be done properly. This paper proposes a novel recognition system of the index finger motion suing a cutting-edge method and its improvements. The proposed system consists of combination of feature extraction method, a dimensionality reduction

Khairul Anam, Adel Al Jumaily, Yashar Maali

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 2, 644–657

Article | 01-March-2015

IRIS-FACE FUSION AND SECURITY ANALYSIS BASED ON FISHER DISCRIMINANT

With the development of society and science technology, the information security becomes more and more important for people and nation. In this paper, we focus on the technology of iris-face fusion in multi-mode sense in order to find an algorithm to get a better recognition performance. Firstly, we introduce the feature extraction of iris and face, and fusion the features using different algorithms. By simulation, we find out the recognition performance with different fusion methods, which

Qihui Wang, Bo Zhu, Yo Liu, Lijun Xie, Yao Zheng

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 387–407

research-article | 30-November-2018

Developing smart Tele-ECG system for early detection and monitoring heart diseases based on ECG signal: progress and challenges

outlier removal process can be seen in Figure 6. Figure 5: Outlier removal using IQR. Figure 6: Beat features before and after outlier removal using IQR. Feature extraction Feature extraction is one of the key aspects of pre-processing techniques, as this process will select the features that will be used by the classification process later on. Therefore, it is essential to extract the best features from the data set, as selecting better features will lead to better outcome during the

Wisnu Jatmiko, M. Anwar Ma’sum, Hanif Arief Wisesa, Hadaiq Rolis Sanabila

International Journal on Smart Sensing and Intelligent Systems, Volume 12 , ISSUE 1, 1–28

Article | 02-April-2020

Research on the Tunnel Geological Radar Image Flaw Detection Based on CNN

He Li, Yubian Wang

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 1, 44–53

Article | 14-October-2020

Hierarchical Image Object Search Based on Deep Reinforcement Learning

classification can be achieved. II. RELATED WORK A. Traditional object detection algorithm Traditional object detection algorithms include primary feature extraction methods such as HOG feature extraction of objects and training SVM classifiers for recognition. Their algorithms are generally divided into three stages (see Figure 1.): Figure 1. Traditional object detection algorithm 1)Select different sliding window frames according to the size of the object, and use the sliding window to select a part

Wei Zhang, Hongge Yao, Yuxing Tan

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 3, 65–72

research-article | 30-November-2020

A face-machine interface utilizing EEG artifacts from a neuroheadset for simulated wheelchair control

includes four parts, i.e., (i) the proposed system, (ii) signal acquisition and preprocessing, (iii) feature extraction and algorithms, and (iv) command translations. The third section presents experimental results and discussions to demonstrate the efficiency of the proposed system and algorithm from the second section for online testing. In the last section, the outcome and outlook of the proposed system will be presented as a conclusion, and future work will be suggested. Research methods

Theerat Saichoo, Poonpong Boonbrahm, Yunyong Punsawad

International Journal on Smart Sensing and Intelligent Systems, Volume 14 , ISSUE 1, 1–10

Research Article | 01-September-2017

DYNAMIC FACE RECOGNITION AND TRACKING SYSTEM USING MACHINE LEARNING IN MATLAB AND BIGDATA

are trained into the databases using machine learning algorithm. The tracking of individuals can be achieved by capturing their images while on the move and comparing them with the values stored in the databases. The detection of facial structure is done with Viola-Jones algorithm which though older is easy and efficient to use and Kanade-Lucas-Tomasi(KLT) algorithm is used for feature extraction . The HOG (Histogram of Oriented Gradients) features are extracted for training.

P.J Leo Evenss, Jennings Mcenroe .S, A.Prabhu Chakkaravarthy

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 163–173

Research Article | 05-September-2018

Multi-algorithmic Palmprint Authentication System Based on Score Level Fusion

Fusion of multiple algorithms utilizes as much information as possible from each algorithm for enhancing the performance of the biometric authentication system. It is a big challenge to formulate a single algorithm for any biometric authentication system to addresses the problem of illumination, orientations and pose variations. The palmprint features are extracted using two feature extraction algorithms namely contourlet transform with principal component analysis and dual-tree complex wavelet

C. Murukesh, G. Arul Elango

International Journal on Smart Sensing and Intelligent Systems, Volume 11 , ISSUE 1, 1–11

Article | 01-September-2015

AUTOMATIC RECOGNITION OF FACIAL EXPRESSION BASED ON COMPUTER VISION

Automatic facial expression recognition from video sequence is an essential research area in the field of computer vision. In this paper, a novel method for recognition facial expressions is proposed, which includes two stages of facial expression feature extraction and facial expression recognition. Firstly, in order to exact robust facial expression features, we use Active Appearance Model (AAM) to extract the global texture feature and optical flow technique to characterize facial expression

Shaoping Zhu

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1464–1483

Article | 01-March-2015

INTELLIGENT DETECTION OF FACIAL EXPRESSION BASED ON IMAGE

Human facial expressions detection plays a central role in pervasive health care and it is an active research field in computer vision. In this paper, a novel method for facial expression detection from dynamic facial images is proposed, which includes two stages of feature extraction and facial expression detection. Firstly, Active Shape Model (ASM) is used to extract the local texture feature, and optical flow technique is determined facial velocity information, which is used to characterize

Shaoping Zhu, Yongliang Xiao

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 581–601

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