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B-cell epitope is the small portion of antigen surface that is identified by antibodies. Epitope prediction is the task of identification of antigen surface in one of the classes of epitopes and non-epitopes. The prediction of B-cell epitopes is affected by different scales (features) of amino acid samples, such as hydrophobicity, polarity and flexibility, and so, it is necessary to utilize an appropriate...
A class imbalance problem often appears in many real world applications, e.g. fault diagnosis, text categorization, fraud detection. When dealing with a large-scale imbalanced dataset, feature selection becomes a great challenge. To confront it, this work proposes a feature selection approach based on a decision tree rule. The effectiveness of the proposed approach is verified by classifying a large-scale...
Human gesture recognition is a rather new field and many challenges, sign language recognition is a concrete example of gesture recognition. In this paper, we study the feasibility and effectiveness of vector machine learning methods, namely Support Vector Machine (SVM), Simplification of Support Vector Machine (SimpSVM) and Relevance Vector Machine (RVM) to the sign language recognition problem....
Concrete can be molded to any shape and size, and once hardened it can withstand tremendous amount of compressive loads. This ability of concrete makes it the most widely used material in construction and thus, a need for identification and prediction of its compressive strength. Nondestructive tests have been solely preferred for this purpose and a drop-impact test machine prototype named; Material...
Texture classification is a problem that has variousapplications such as remote sensing and forest speciesrecogni- tion. Solutions tend to be custom fit to the datasetused but fails to generalize. The Convolutional NeuralNetwork (CNN) in combination with Support Vector Machine(SVM) form a robust selection between powerful invariantfeature extractor and accurate classifier. The fusion ofexperts provides...
Peak ground acceleration (PGA) is equal to the maximum ground acceleration that occurred during earthquake shaking at a location and the design basis earthquake ground motion is often defined in terms of PGA. In this paper, three intelligent methods are proposed for predicting of PGA in regions where PGA value is greater than 0.5g. These knowledge base methods are Adaptive Network Based Fuzzy Inference...
Online shopping is one of the most comfortable ways to shop in this new era of technology. People buy online products frequently and post their reviews about the products they have used. The viewpoint of the user will be in the form of tweets or product reviews which they post in an e-commerce site. These reviews will have significant role in deciding how far the products have been placed in peoples...
The performance of speech emotion classifiers greatly degrade when the training conditions do not match the testing conditions. This problem is observed in cross-corpora evaluations, even when the corpora are similar. The lack of generalization is particularly problematic when the emotion classifiers are used in real applications. This study addresses this problem by combining active learning (AL)...
In this paper, a blind bandwidth extension algorithm for music signals has been proposed. This method applies the K-means algorithm to firstly cluster audio data in the feature space, and constructs multiple envelope predictors for each cluster accordingly using Support Vector Regression (SVR). A set of well-established audio features for Music Information Retrieval (MIR) has been used to characterize...
When emotion recognition systems are used in new domains, the classification performance usually drops due to mismatches between training and testing conditions. Annotations of new data in the new domain is expensive and time demanding. Therefore, it is important to design strategies that efficiently use limited amount of new data to improve the robustness of the classification system. The use of...
We propose an image aesthetic quality assessment algorithm, which considers personal taste in addition to generally perceived preference. This problem is formulated by a combination of two different learning frameworks based on support vector machines—Support Vector Regression (SVR) and Ranking SVM (R-SVM), where SVR learns a general model based on public datasets and R-SVM adjusts the model to accommodate...
Predicting a person's gender based on the iris texture has been explored by several researchers. This paper considers several dimensions of experimental work on this problem, including person-disjoint train and test, and the effect of cosmetics on eyelash occlusion and imperfect segmentation. We also consider the use of multi-layer perceptron and convolutional neural networks as classifiers, comparing...
The Classroom Attentiveness Classification Tool (ClassACT) is a system designed to monitor student attentiveness in a variety of instructional phases within the learning environment: lectures, group work, assessments, etc. By collecting information about the user, the user's environment, and the device itself via the various sensors built in to the tablet, processing the data, and then passing it...
Optical Character Recognition can be defined as the process of detecting and identifying text from a scanned image. There are a number of techniques by which recognition is carried out in several languages. The main steps of optical character recognition are Line segmentation, Word segmentation, Character segmentation and Character recognition. Character recognition has two phases: Feature extraction...
This paper presents a novel technique of image classification using BOVW model. The entire process first involves feature detection of images using FAST, the choice made in order to speed up the process of detection. Then comes the stage of feature extraction for which FREAK, a binary feature descriptor is employed. K-means clustering is then applied in order to make the bag of visual words. Every...
Keystroke dynamics is an effective behavioral biometric for user authentication at a computer terminal. While many distinctive features have been used for the analysis of acquired user patterns and verification of users transparently, a group of features such as Shift and Comma has always been overlooked and treated as noise. In this paper, we define these normally ignored features as secondary features...
In this study, an artificial intelligence (AI) intrusion detection system using a deep neural network (DNN) was investigated and tested with the KDD Cup 99 dataset in response to ever-evolving network attacks. First, the data were preprocessed through data transformation and normalization for input to the DNN model. The DNN algorithm was applied to the data refined through preprocessing to create...
Multi-Label classification aims to classify an example that can belong to many classes. Although One-versus-All (OVA) is the most common approach, our prior work has shown that the proposed One-versus-One (OVO) always gives higher prediction accuracy than OVA. However, OVO requires an extremely high computational cost when there are a large number of labels. In this paper, we apply our OVO SVMs on...
Face recognition system is used for the identification and verification of a face from a video or digital image. In the first phase, Viola Jones algorithm is used to detect and crop face region automatically from image/video frame. The second phase is to recognize the face of a person, in our proposed method Bag of Word technique used to extract features from an image which uses SURF for interest...
This paper proposes a new scheme for hyperspectral image classification through k-means clustering. The scheme includes three steps. Firstly, principal component analysis (PCA) is utilized for dimension reduction of the hyperspectral image. Secondly, the reduced features are clustered using k-means clustering algorithm and subsequently the clusters are trained separately by multi-class support vector...
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