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The problem of object detection in image and video has been treated by a large number of researchers. Many design factors degrade the reliability of the problem solutions, such as manual modeling of the object, manual features selection, handcrafting architecture, and learning algorithm selection. Here, a generalized object detection and localization system is presented. It has the ability to learn...
This paper compares performance of several classifiers provided in WEKA such as Bayes, decision tree and classification rules in classifying student's learning style. The student's preferences and behavior while using e-learning system have been observed and analyzed and twenty attributes have been selected to map into Felder Silverman learning style model. There are four learning dimensions in Felder...
The success of any statistical steganalysis algorithm depends on the choice of features extracted and the classifier employed. This paper proposes steganalysis using random forests (SURF) employing HCS (Huffman Code Statistics) features and FR Index (ratio of File size to Resolution). The proposed algorithm is validated over an image database of over 30,000 images spanning various sizes, resolutions,...
Stemming is a fundamental step in processing textual data preceding the tasks of text mining, Information Retrieval (IR), and natural language processing (NLP). The common goal of stemming is to standardize words by reducing a word to its base (root or stem), thus can be also considered a feature reduction technique. This paper aims at presenting a new dictionary free, content-based Arabic stemmer...
Signature is a popular method of seeking approval and authentication between various parties in many transaction applications. Signature pattern recognition is done by processing a set of data that consists of (x, y) coordinates, representing online signature. Particle Swarm Optimisation technique is used to find and analyse the baseline feature that exists within the signature. Signatures were taken...
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