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352 articles for “n-dimensional”
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Research ArticleOpen accessIn the abstractA Novel SIFT-SVM Approach for Prostate Cancer DetectionSwetha Parvatha Reddy Chandrasekhara, Mohan Govindsa Kabadi, SrivinayProstate cancer is a major cause of concern in male population as it is said to affect 1 in every 7 men in their lifetime. The number of cases being registered for prostate cancer and its mortality rates are increasing yearly at an alarming rate. Due to the high resolution and multi-dimensionality of the Magnetic Resonance Imaging (MRI) images, proper … …Journal of Computer Science, Vol. 16, Issue 12 · 22 Dec 2020 · 7,530 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Implementation of Support Vector Machine on the Multi-Label Classification of English-Translated Quranic VersesSatrio Adi Prabowo, Adiwijaya, Mohamad Syahrul Mubarok et al.One of the attempts to understand the meaning and content of the Quran, the central religious text of Islam, is the topic classification of Quranic verses. Verse topic classification aims to help the reader, so he can easily and quickly find information or knowledge contained in the Quran. In this paper, we build a classification model for the topics of … …Journal of Computer Science, Vol. 15, Issue 12 · 19 Dec 2019 · 7,793 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,761 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Breast Tumor in Mammogram Images Using Unsupervised Feature LearningAidarus M. Ibrahim, Baharum Baharudin, Abas Md Said, P. N. HashimahIn this study, we propose a learning-based approach using feature learning to minimize the manual effort required to extract features. Firstly, we extracted features from equally spaced sub-patches covering the input Region of Interest (ROI). The dimensionality of the extracted features is reduced using max-pooling. Furthermore, spherical k-means clustering coupled with max pooling (k-means-max pooling) is compared with well-known feature … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 13 May 2016 · 7,503 accessesView PDFCite
Research ArticleOpen accessIn the abstractExtended Kalman Filter versus Newton-Lowe's Method for Robot Pose EstimationMohammad Ehab RagabIn this work, we study the pose estimation problem of anautonomous mobile robot. Particularly, we compare the Extended Kalman Filter (EKF) to Lowe's method based on the iterative Newton's method for solving a system of nonlinear equations. Although the EKF is recursive which renders it suitable for the real-time problem at hand, Lowe's method has much less dimensionality. This is … …Journal of Computer Science, Vol. 11, Issue 7 · 5 Nov 2015 · 6,940 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Distinguishability Based Weighted Feature Selection Algorithms for Improved Classification of Gene Microarray DatasetJ. Jeyachidra, M. PunithavalliData mining played vital role in comprehending, analyzing, understanding and interpreting microarray technology expression data. That includes search for genes that had similar or correlated patterns of expression. For that, the feature selection was one of the frequently used important techniques for data preprocessing. Many feature selection algorithms had been developed. Yet the persisting problem was in selecting optimal subset … …Journal of Computer Science, Vol. 11, Issue 2 · 2 Feb 2015 · 6,380 accessesView PDFCite
Research ArticleOpen accessIn the abstractRADIUS BASED BLOCK LOCAL BINARY PATTERN ON T-ZONE FACE AREA FOR FACE RECOGNITIONMd. Jan Nordin, Abdul Aziz K. Abdul Hamid, Sumazly Ulaiman, R. U. GobithaasanThis study presents a comparison of recognition performance between feature extraction on the T-Zone face area and Radius based block on the critical point. A T-Zone face image is first divided into small regions where Local Binary Pattern (LBP) histograms are extracted and then concatenated into a single feature vector. This feature vector will further reduce the dimensionality scope by … …Journal of Computer Science, Vol. 10, Issue 12 · 27 Dec 2014 · 7,971 accessesView PDFCite
Research ArticleOpen accessIn the abstractA COMPARATIVE STUDY OF COMBINED FEATURE SELECTION METHODS FOR ARABIC TEXT CLASSIFICATIONAisha Adel, Nazlia Omar, Adel Al-ShabiText classification is a very important task due to the huge amount of electronic documents. One of the problems of text classification is the high dimensionality of feature space. Researchers proposed many algorithms to select related features from text. These algorithms have been studied extensively for English text, while studies for Arabic are still limited. This study introduces an investigation … …Journal of Computer Science, Vol. 10, Issue 11 · 20 Dec 2014 · 8,439 accessesView PDFCite
Research ArticleOpen accessIn the abstractTHE HIGH VOLUME REUSE OF HYBRID BIOMASS ASH AS A PRIMARY BINDER IN CEMENTLESS MORTAR BLOCKCheah Chee Ban, Noor Shazea Ahmad Nordin, Part Wei Ken et al.High Calcium Wood Ash (HCWA) and Pulverised Fuel Ash (PFA) are by-products from the wood biomass and coal energy production which are produced in large quantity with combined annual production of 500 million tonnes. This poses a serious problem for disposal of the waste material especially at places where land is scarce. The prescribed study was aimed to examine the … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 29 May 2014 · 7,168 accessesView PDFCite
Research ArticleOpen accessIn the abstractBRAIN TUMOR CLASSIFICATION BASED ON CLUSTERED DISCRETE COSINE TRANSFORM IN COMPRESSED DOMAINV. Anitha, S. MurugavalliThis study presents a novel method to classify the brain tumors by means of efficient and integrated methods so as to increase the classification accuracy. In conventional systems, the problem being the same to extract the feature sets from the database and classify tumors based on the features sets. The main idea in plethora of earlier researches related to any … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,537 accessesView PDFCite