[PDF] Top 20 <p>An automated mammogram classification system using modified support vector machine</p>

... Radiologists analyze ROI found on mammograms by examining morphological features, such as size, margin and shape of the ROI; this helps them to differentiate between normal and abnormal mammograms and also to ... See full document

... In computer vision, motion analysis of the human body usually involves segmenting, tracking and recovering the human body motion in an image sequence. Fig. 1 shows the system architecture used within this study. ... See full document

... engineering, machine learning and artificial intelligence focus on the interactions between human's languages and computer machines, by simplicity , how the computers will understand and analyze huge amounts of ... See full document

... person using dissimilar poses and ...different classification approaches are used for face ...internet. Support Vector Machine (SVM) is used as both binary classification and ... See full document

... component vector or a non-numeric syntactic portrayal word, which portray properties of the depicted ...acknowledged system of shape ...component vector, or a non-numeric vector depiction ... See full document

... limbic system, then extending toward neocortical ...evaluated using visual rating scales, linear or volumetric measurements, and voxel-based ...Recent classification methods have been developed that ... See full document

... existing system using Clinical Decision Support System based on Support Vector Machine ...are using Support Vector Machine Data Mining ... See full document

... beat classification presented thorough experimental exploration of the RVM capabilities for ECG ...of classification accuracy are evaluated: 1) by automatically detecting the best discriminating features ... See full document

... to machine learning, we used Anaconda3 for Python for implementation of this ...by using Tensorflow for detecting license plate of various vehicles and Tesseract engine is used for recognizing characters ... See full document

... In Table 1, a performance comparison of 11 recent works (including this work) related to CADx systems is shown. It should be noted that in the works presented in Table 1, different methodologies were used to create the ... See full document

... AES was developed by web application in C# which used to implement the described algorithms in previous section. Html & css (bootstrap framework) were used for structuring each page, and also styling of each page. ... See full document

... various machine learning algorithms and classified based on their color and texture ...two machine learning algorithms are used namely K-Nearest Neighbours, Support Vector ... See full document

... a machine to improve its own performance through the use of a software that employs artificial intelligence ...data. Support vector machine (SVM) is the machine learning algorithm used ... See full document

... a machine learning system and integrate this enriched information as features to learn an SVM classifier (3) we assume that the cate- gory of a query is closely related to the category of the corresponding ... See full document

... an early stage. Subsequent treatment is essential for affected patients to preserve their vision. Manual analysis of the eye is time consuming and the accuracy of the parameter measurements also varies with different ... See full document

... Mammography classification using support vector machine with image enhancement and three types of extracted features that we proposed in our framework is the main contribution of this ... See full document

... text classification and structuring of this e-content has become the need of the ...text classification is the process of assigning a category or categories to a new test document from one or more ... See full document

... the system is points/per ...the classification which will give the best results compare to the traditional ...the Support Vector Machine for classifying the events ... See full document

... SVM is a discriminative classifier and follows supervised learning. SVM can be implemented efficiently and it’s also proved its excellent performance in high dimensional problems and small data sets, hence it is chosen ... See full document

... any system that analyzes large quantities of natural language text and detects lexical or linguistic usage patterns in an attempt to extract probably useful information ...Text classification which is ... See full document