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272 results for “Co-Occurrence”
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Research ArticleOpen accessPhrase in the titleA Semantic Image Retrieval Technique Through Concept Co-occurrence Based Database Organization and DeepLab SegmentationR. Jayadevan, V.S. SheebaIn this paper, a semantic image retrieval technique that efficiently depicts users’ perspective is proposed. It primarily aims in the representation of contextual diversity of the user through a high level semantic segmentation technique called DeepLab-V3+. An online user interactive step is also included during the retrieval process. The significance of intra-concept variation in image retrieval is clearly presented in … …Journal of Computer Science, Vol. 16, Issue 1 · 11 Jan 2020 · 6,996 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDirect Sequence and Frequency Hopping Signals Classification Based on Co-Occurrence Matrix and Clustering TechniquesHaidy S. Fouad, Hend A. Elsayed, Shawkat K. GirgisSpread Spectrum techniques (SS) were first developed for military applications, but currently, they have commercial applications. SS provides secure communication and allows multiple accesses for same radio spectrum. So, most Wireless Local Area Network (WLAN) systems use it, as do Cognitive Radios (CR), space systems and Global Positioning Systems (GPS). Direct Sequence Spread Spectrum (DSSS) and frequency hopped spread spectrum … …Journal of Computer Science, Vol. 15, Issue 1 · 10 Jan 2019 · 8,203 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA 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 · 6,602 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFeature Fusion Technique for Colour Texture Classification System Based on Gray Level Co-occurrence MatrixA. Suresh, K. L. ShunmuganathanIn this study, an efficient feature fusion based technique for the classification of colour texture images in VisTex album is presented. Gray Level Co-occurrence Matrix (GLCM) and its associated texture features contrast, correlation, energy and homogeneity are used in the proposed approach. The proposed GLCM texture features are obtained from the original colour texture as well as the first non … …Journal of Computer Science, Vol. 8, Issue 12 · 5 Jan 2013 · 6,615 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleGray-Level Co-occurrence Matrix Bone Fracture DetectionHum Yan Chai, Lai Khin Wee, Tan Tian Swee et al.Problem statement: Currently doctors in orthopedic wards inspect the bone x-ray images according to their experience and knowledge in bone fracture analysis. Manual examination of x-rays has multitude drawbacks. The process is time-consuming and subjective. Approach: Since detection of fractures is an important orthopedics and radiologic problem and therefore a Computer Aided Detection(CAD) system should be developed to improve the … …American Journal of Applied Sciences, Vol. 8, Issue 1 · 31 Jan 2011 · 8,968 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePERFORMANCE ANALYSIS OF GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURE FEATURES FOR GLAUCOMA DIAGNOSISSakthivel Karthikeyan, N. RengarajanGlaucoma is a multifactorial optic neuropathy disease characterized by elevated Intra Ocular Pressure (IOP). As the visual loss caused by the disease is irreversible, early detection is essential. Fundus images are used as input and it is preprocessed using histogram equalization. First order features from histogram and second order features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 24 Dec 2013 · 7,326 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleContent Based Medical Image Retrieval with Texture Content Using Gray Level Co-occurrence Matrix and K-Means Clustering AlgorithmsB. Ramamurthy, K. R. ChandranProblem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies … …Journal of Computer Science, Vol. 8, Issue 7 · 24 May 2012 · 7,448 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePLANT RECOGNITION USING STEREO LEAF IMAGE USING GRAY-LEVEL CO-OCCURRENCE MATRIXHermawan Syahputra, Agus Harjoko, Retantyo Wardoyo, Reza PulunganAdequate knowledge, such as information about the unique characteristics of each plant, is necessary to identify plant. Researchers have made plant recognition based on leaf characteristics. The leaf image-based plant recognition in view of different angles is a new challenge. In this study, the research on the plant recognition was conducted based on leaf images resulted from 3D stereo camera. … …Journal of Computer Science, Vol. 10, Issue 4 · 24 Dec 2013 · 8,116 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification Model for Hotspot Occurrences Using Spatial Decision Tree AlgorithmImas Sukaesih Sitanggang, Razali Yaakob, Norwati Mustapha, A. N. AinuddinDeveloping a predictive model for forest fires occurrence is an important activity in a fire prevention program. The model describes characteristics of areas where fires occur based on past fires data. It is essential as an early warning system for preventing forest fires, thus major damages because of fires can be avoided. This study describes the application of data mining … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 7,224 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOccurrences Algorithm for String Searching Based on Brute-force AlgorithmAbabneh Mohammad, Oqeili Saleh, Rawan A. AbdeenThis study proposes a string searching algorithm as an improvement of the brute-force searching algorithm. The algorithm is named as, Occurrences algorithm. It is based on performing preprocessing for the pattern and for the text before beginning to search for the pattern in the text. …Journal of Computer Science, Vol. 2, Issue 1 · 31 Jan 2006 · 8,077 accessesView PDFCite