Research ArticleOpen accessIn the abstractSecurity Guard Robot Detecting Human Using Gaussian Distribution Histogram MethodMbaitiga ZacharieProblem statement: The purpose of any robotic is to perform tasks that a human would prefer not to do or hopefully do it with precision in order to avoid mistakes or when a human is out of duty due to fatigue or health reasons. The research into human detection into images has paid the way be aware of what is … …Journal of Computer Science, Vol. 6, Issue 10 · 5 Aug 2010 · 7,056 accessesView PDFCite
Research ArticleOpen accessIn the abstractErythema Multiforme Minor: A RevisionL. R. Oliveira, S. ZucolotoThe term Erythema Multiforme (EM) includes a wide and controversial variety of clinical expressions at the present time. This study revises the EM minor characteristics according to the most important publications found in literature. Erythema Multiforme is a distinct dermatologic hypersensitivity pathology characterized by cutaneous or mucous lesions and eventually it can also involve both. In their more severe forms, … …American Journal of Infectious Diseases, Vol. 4, Issue 4 · 31 Dec 2008 · 7,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Squamous Cell Carcinoma Based On Color and Textural Features in Microscopic Images of Esophagus TissuesP. S. Hiremath, Y. Humnabad Iranna, Jagadeesh D. PujariThis paper presents a method for feature extraction using color and texture from microscopic images of esophagus tissues obtained from the abnormal regions of human esophagus detected through endoscopy. This method is used for classification of Squamous Cell Carcinoma (SCC) of esophagus, namely, poorly differentiated SCC, moderately differentiated SCC, and well differentiated SCC. Three different color spaces, namely, HSV, YCbCr, … …Journal of Computer Science, Vol. 3, Issue 7 · 31 Jul 2007 · 6,874 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Mining: A Preprocessing EngineLuai A. Shalabi, Zyad Shaaban, Basel KasasbehThis study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A new matrix was designed … …Journal of Computer Science, Vol. 2, Issue 9 · 30 Sep 2006 · 34,390 accessesView PDFCite