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For the sake of improving the precision of speech emotion recognition, this paper proposed a novel speech emotion recognition approach based on Gaussian Kernel Nonlinear Proximal Support Vector Machine (PSVM) to recognize four basic human emotions (angry, joy, sadness, surprise). Firstly, preprocess speech signal containing sampling, quantification, pre-emphasizing, framing, adding window and endpoint...
Remote access Trojans (RATs) are used by attackers to compromise and control the victim machine. In this work, a novel Network-based framework is introduced for detecting RAT bots based on data mining techniques. Several machine learning (ML) techniques are used to differentiate between benign and RAT infected machines. Various performance measurements are used to evaluate the performance of the proposed...
The bank client identity verification system developed in the course of the IDENT project is presented. The total number of five biometric modalities including: dynamic signature proofing, voice recognition, face image verification, face contour extraction and hand blood vessels distribution comparison have been developed and studied. The experimental data were acquired employing multiple biometric...
Protein sequence classification is increasingly crucial in the current “biological information sciences” epoch, where researchers hammer at functional genomics and proteomics technologies for predicting the function of large-scale new proteins. This has sparked interest in the methods which do not rely on traditional sequence alignment, but prefer machine learning approaches. In this paper, we present...
Software-defined networks (SDN) are vulnerable to most of the attacks that traditional networks are vulnerable to. In addition, SDN has introduced new vulnerabilities through its unique architecture such as those related to the southbound and northbound controller interfaces. In this paper, we introduce a lightweight flow-based Intrusion Detection System (IDS) that periodically gathers statistical...
The new social media have become popular for information spreading, allowing online users to publish latest events and personal opinions. However, massive spam comments seriously decrease users' reading experience. To detect spam comments in Chinese social media, we employ semantic analysis to build the self-extensible dictionary which updates and extends itself with new cyber words automatically...
There is an increasing trend for finding solutions to interact with computers, and computers in turn interact with people. For an effective human-computer intelligent interaction, this must be natural, the computer interpreting the user's emotional state to adapt to its behavior, giving an appropriate response to those emotions. This paper presents a software application for emotional states recognition...
It is widely accepted that feature extraction is quite possibly the most critical step in computer vision. Typically, feature extraction is performed using a method such as the histogram of oriented gradients. In recent years, a shift has occurred from human to machine learned features, e.g., convolutional neural networks (CNNs) and Evolution-COnstructed (ECO) features. An advantage of our improved...
Stereo matching is an active research area in computer vision for decades. This paper introduces a new disparity map estimation algorithm based on image segments. The reference image is segmented using hill-climbing algorithm. The initial disparity map is estimated Scale Invariant Feature Transform (SIFT) feature points matching between two stereo images in each segment by Sum of Absolute Difference...
Traumatic and degenerative shoulder pathologies of which treatment strategy and success depends on correct diagnosis are more commonly encountered at the present time. The aim of this study is to help clinicians by using computer based decision support systems to diagnose correctly the degenerative and traumatic conditions of shoulder from MR images which is not an easy task in practice. Image patches...
Reliable automatic ship detection in Synthetic Aperture Radar (SAR) imagery plays an important role in the surveillance of maritime activity. Apart from the well-known Spectral Residual (SR) and CFAR detector, there has emerged a novel method for SAR ship detection, based on the deep learning features. Within this paper, we present a framework of Sea-Land Segmentation-based Convolutional Neural Network...
Scoring facial wrinkles is a crucial process to specify exact treatment for wrinkles or to understand the effectiveness of the applied treatment to wrinkles. In this study, only forehead wrinkles are examined instead of the whole facial wrinkles. Detection and quantification of the forehead wrinkles are tried to be performed automatically by computers. For this purpose, the features are extracted...
Extracting opinion words and product features is an important task in many sentiment analysis applications. Opinion lexicon also plays a very important role because it is very useful for a wide range of tasks. Although there are several opinion lexicons available, it is hard to maintain a universal opinion lexicon to cover all domains. So, it is necessary to expand a known opinion lexicon that are...
Community detection is a substantial technique to find out the relationship between nodes in complex networks. By understanding the behavior of elements in a community, one can predict the overall feature of the large scale social network. Detecting different communities in large scale network is a challenging task due to huge data size associated with such network. The main purpose of this paper...
Timely and accurate diagnosis of intraabdominal organ injuries due to trauma is critical. Computer Assisted Detection (CAD) systems are rapidly developing techniques to segment the organs or to detect the pathologies in medical applications; either automatically or semi-automatically. In this work, our aim is to propose and validate a CAD system which classifies injured kidney in Computed Tomography...
Recruiters evaluate and filter job seekers, ranking them on various criteria. This includes how much of the required and desired requirements are satisfied, ensuring the candidate is the “best match” to vacancy. However, most vacancies do not classify the set of skills as required and desired explicitly. Required skills are those skills a job seeker must have in order to be considered for the job...
Big data technology is used to integrate, clean up and analyze the data of student management system, educational administration system, and campus card consumption system and so on in this paper. The characteristics of high risk students are extracted and selected, and the prediction model is constructed, which can be used to predict the high risk students scientifically, reasonably and effectively,...
SIFT-based identification techniques have been broadly criticised in biometrics due to its high false matching rate. To overcome this weakness, a new method for SIFT-based palmprint matching, called the Self Geometric Relationship-based matching (SGR-Matching) is presented. While existing matching techniques consider only the relationship between the SIFT-points of the query image on one hand and...
Dimensionality reduction is an important factor in fault diagnosis, when dealing with a high-dimensional feature space, since it decreases the computational burden and the model complexity. This paper focuses on the development and comparison of several state-of-the-art linear dimensionality reduction techniques to provide discriminant features for the process fault diagnosis. These techniques, including...
Content-based image retrieval is a technology that is used to identify similar images based on their visual content. Relevant images are found by employing methods that rank images and show the top-ranked images. One important query pertaining to image retrieval methods is regarding as to how to rank the results. This paper proposes a new method based on an unsupervised Hopfield neural network that...
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