218 results for “Feature Extraction”

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Research ArticleOpen accessIn the abstractAdverse Drug Reaction Detection Using Latent Semantic AnalysisAhmed Adil Nafea, Nazlia Omar, Mohammed M. AL-AniDetecting Adverse Drug Reactions (ADRs) is one of the important information for determining the view of the patient on one drug. Most studies have investigated the extraction of ADRs from social networks, in which users share their opinion on a particular medication. Some studies have used trigger terms to detect ADRs. Such studies showed remarkable performance in terms of extracting … …Journal of Computer Science, Vol. 17, Issue 10 · 28 Oct 2021 · 7,816 accessesView PDF Cite

Research ArticleOpen accessIn the abstractStructural Geodesic-Tchebychev Transform: An Image Similarity Measure for Face RecognitionAli Nadhim Razzaq, Zahir M. Hussain, Hind Rustum MohammedThis work presents a new holistic measure for face recognition. Face recognition involves three steps: Face Detection, Feature Extraction and Matching. In the face detection process to identify the face area in face images, Viola-Jones algorithm has been used. Feature extraction is based on performing double-transformation, where discrete Tchebychev transform is performed on the geodesic distance transform of the grayscale … …Journal of Computer Science, Vol. 12, Issue 9 · 29 Nov 2016 · 7,645 accessesView PDF Cite

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 PDF Cite

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 PDF Cite

Research ArticleOpen accessIn the abstractAn Innovative Approach for Person Identification by Detection and Extraction of Optic Disc from Retina and Concha from EarC. Malathy, A. K. Sadiq, K. AnnapuraniPerson identification based on unimodal biometric system suffers from noise, intra class similarity, non universality, distinctiveness and spoof attacks. To alleviate the problem faced in unimodal biometric system biometric traits are combined in multimodal biometric system. In this study a new approach, to improve the recognition rate, reduces computational complexity and storage space is presented. Distinct method of person identification … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Sep 2014 · 6,559 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid Approach for Detection and Recognition of VehiclesK. S. Selvanayaki, Rm. SomaSundaramOn road vehicles have increased in numbers and monitoring them is a challenging task. In common areas of public crowd people and vehicles are common objects for monitoring. The proposed system aims at detecting number plate information indicating the possibility for security relevant issues. Existing system performs recognition mainly by using license plate alone. Addition of the features (logo, colour, … …Journal of Computer Science, Vol. 11, Issue 2 · 6 Sep 2014 · 7,436 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCLASSIFICATION OF MICROCALCIFICATION BASED ON WAVE ATOM TRANSFORMA. Rajesh, Mohan EllappanBreast cancer is a serious problem for women in the world. It is the most common form of cancer diagnosed in woman, with one in nine women expected to be diagnosed with some form of cancer in their life-time. It is second only to lung cancer in cancer related deaths. Statistics shows that the case of breast cancer in the … …Journal of Computer Science, Vol. 10, Issue 8 · 5 Apr 2014 · 6,523 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA NOVELTY APPROACH OF SPATIAL CO-OCCURRENCE AND DISCRETE SHEARLET TRANSFORM BASED TEXTURE CLASSIFICATION USING LPBOOSTING CLASSIFIERC. Vivek, S. AudithanRecently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial co-occurrence with discrete shearlet transformation through the LPboosting classification. It can be considered as a frame through … …Journal of Computer Science, Vol. 10, Issue 5 · 11 Jan 2014 · 6,608 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFEATURE DIMENSION REDUCTION FOR EFFICIENT MEDICAL IMAGE RETRIEVAL SYSTEM USING UNIFIED FRAMEWORKYogapriya Jaganathan, Ila VennilaFeature dimensionality reduction problem is a major issue in Content Based Medical Image Retrieval (CBMIR) for the effective management of medical images with the support of visual features for the purpose of diagnosis and educational research field. The proposed CBMIR is used a unified approach based on extraction of visual features, optimized feature selection, classification of optimized features and similarity … …Journal of Computer Science, Vol. 9, Issue 11 · 24 Sep 2013 · 6,989 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn integrated Framework Based on Texture Features, Cuckoo Search and Relevance Vector Machine for Medical Image Retrieval SystemYogapriya Jaganathan, Ila VennilaAs medical images are widely used in healthcare applications, Content Based Medical Image Retrieval (CBMIR) system is needed for physicians to convey effective decisions to patients and for medical research students to learn imaging characteristics for their extensive research based on visual features. However the performance of the retrieval is restricted due to high feature dimensionality of visual features. To … …American Journal of Applied Sciences, Vol. 10, Issue 11 · 24 Sep 2013 · 6,882 accessesView PDF Cite