Research ArticleOpen accessIn the keywordsAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSoft Clustering Based Exposition to Multiple Dictionary Bag of WordsK. S. Sujatha, B. VinodObject classification is a highly important area of computer vision and has many applications including robotics, searching images, face recognition, aiding visually impaired people, censoring images and many more. A new common method of classification that uses features is the Bag of Words approach. In this method a codebook of visual words is created using various clustering methods. For increasing … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,389 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFetal Electrocardiogram Extraction Using Let TechniquesS. Hemajothi, K. Helen PrabhaFetal Electrocardiogram Extraction (FECG) identifies the congenital heart problems at the earlier stage. The major problem in the non invasive procedure is the extraction of FECG from Maternal ECG (MECG) and many interferences. The proposed methods (i) Combination of Adaptive Neuro Fuzzy Inference (ANFIS) and Fractional spline wavelet (ii) Combination of Fractional spline wavelet and ANFIS (iii) Combination of ANFIS … …Journal of Computer Science, Vol. 8, Issue 9 · 16 Aug 2012 · 7,311 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSurface Electromyography-Based Facial Expression Recognition in Bi-Polar ConfigurationMahyar Hamedi, Sh-Hussain Salleh, Tan Tian Swee, KamarulafizamProblem statement: Facial expression recognition has been improved recently and it has become a significant issue in diagnostic and medical fields, particularly in the areas of assistive technology and rehabilitation. Apart from their usefulness, there are some problems in their applications like peripheral conditions, lightening, contrast and quality of video and images. Approach: Facial Action Coding System (FACS) and some … …Journal of Computer Science, Vol. 7, Issue 9 · 25 Jul 2011 · 9,943 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Computational Optimized Extended Model for Mineral Potential Mapping Based on WofE MethodZiaii Mansour, Pouyan Ali, Ziaei MahdiThe multivariate fuzzy-c-means classifier is used to model extended weight of evidence (WofE) considering predictor maps. Approaches to mineral potential mapping based on WofE modeling generally use binary maps, whereas, real-world geospatial data are mostly multi-class or fuzzy-class in nature. The consequent reclassification of fuzzy-class maps into binary maps is a simplification that might result in a loss of information. … …American Journal of Applied Sciences, Vol. 6, Issue 2 · 28 Feb 2009 · 7,561 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDirect Model Reference Adaptive Controller Based-On Neural-Fuzzy Techniques for Nonlinear Dynamical SystemsHafizah Husain, Marzuki Khalid, Rubiyah YusofThis paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase, similarity index-based fuzzy c-means clustering technique extracts the fuzzy rules in the premise part for the neural-fuzzy controller. This technique enables the recruitment … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 6,939 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMemory Convergence and Optimization with Fuzzy PSO and ACSSubhash C. Pandey, Dr. P. MisraAssociative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this study, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. A Fuzzy … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,169 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Self-Adaptive Neuro Fuzzy Inference System for the Removal of Non-Linear Artifacts from the Respiratory SignalA. Bhavani Sankar, D. Kumar, K. SeethalakshmiProblem statement: In this study, a new ANFIS-based adaptive filter is proposed to remove the non-linear artifacts from the respiratory signal measured using MEMS based accelerometer sensor. The data recorded from the abdomen movement includes the respiratory signal, electromyogram, 50Hz power line interference and the random electrode noise. In order to avoid convergence into local extremes, the system employs ANFIS … …Journal of Computer Science, Vol. 8, Issue 5 · 16 Feb 2012 · 6,891 accessesView PDFCite