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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...
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...
This work addresses Transfer Learning via Convolutional Neural Networks (CNN's) for the automated classification of colonic polyps in eight HD-endoscopic image databases acquired using different modalities. For this purpose, we explore if the architecture, the training approach, the number of classes, the number of images as well as the nature of the images in the training phase can influence the...
Binary Relevance is a well-known framework for multi-label classification, which considers each class label as a binary classification problem. Many existing multi-label algorithms are constructed within this framework, and utilize identical data representation in the discrimination of all the class labels. In multi-label classification, however, each class label might be determined by some specific...
In this paper, we discuss a novel approach to incrementally construct a rule ensemble. The approach constructs an ensemble from a dynamically generated set of rule classifiers. Each classifier in this set is trained by using a different class ordering. We investigate criteria including accuracy, ensemble size, and the role of starting point in the search. Fusion is done by averaging. Using 22 data...
This paper presents a user authentication system based on mouse movement data. An available logging tool named Recording User Input (RUI) is used to collect three types of mouse actions — Mouse Move, Point-and-Click on Left or Right mouse button and Drag-and-Drop. Collected data are divided into N-number of blocks consisting of specific number of actions. From each block seventy four features are...
Microblog, especially Twitter, have become an integral part of our daily life, where millions of users sharing their thoughts daily because of its short length characteristics and simple manner of expression. Monitoring and analyzing sentiments from such massive Twitter posts provide enormous opportunities for companies and other organizations to estimate the user acceptance of their products and...
Intrusion Detection System (IDS) is an essential method to protect network security from incoming on-line threats. Machine learning enable automates the classification of network patterns. This paper review the learning and detection methods in IDS, discuss the problems with existing intrusion detection systems and review data reduction techniques used in IDS in order to deal with huge volumes of...
The state-of-the-art image classification methods require an intensive learning stage and a considerable amount of training images. Recently, with the introduction of these models (and in particular convolutional neural network (CNN)), it is believed that the best solution to achieve a system with high performance on scene classification is to learn deep scene features using CNN. While this can be...
It is important to provide detailed and instructive feedback in computer assisted pronunciation training (CAPT) system. However the feedback is limited to the accuracy of the erroneous tendency detection. This paper proposed to apply senone log-likelihood ratio based articulatory features (AFs) to improve pronunciation erroneous tendency (PET) detection performance. Also the feedback information of...
Motor imagery brain-computer interfaces (MIBCI) use hand or foot MI to control computers. However, MIBCI control accuracy is low. Previously, we determined that using max power in the mu band method, i.e., the peak trace method (PTM), improves event-related desynchronization (ERD) detection accuracy. Control accuracy may be improved by improving ERD detection accuracy in an MIBCI. In this study, we...
This paper presents a data-driven approach towards the modeling of agent behaviors in a full-fledged, commercial off-the-shelf simulation milieu for tactical military training. The modeling approach employs machine learning to identify behavioral rules and patterns in data. Potential advantages of this approach are that it may improve modeling efficiency and, perhaps more importantly, increase the...
The purpose of this work is to evaluate possible minimisation of the time needed for expansion of the scope of a CNN (convolutional neural network) classifier without the need to fully re-train it. We investigate the effects of applying k-NN (k-Nearest Neighbours) based classification and transfer learning (via fine-tuning) for the purpose of adding new classes to an existing deep convolutional neural...
Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), is proposed for detection of melanoma lesions. Clinical (non-dermoscopic) images are used in the proposed system, which could assist a dermatologist in early diagnosis of this type of skin cancer. In the proposed...
In this paper, a complete voiceprint recognition based on Matlab was realized, including speech processing and feature extraction at early stage, and model training and recognition at later stage. For speech processing and feature extraction at early stage, Mel Frequency Cepstrum Coefficient (MFCC) was taken as feature parameter. For speaker model method, DTW model was adopted to reflect the voiceprint...
In this paper, we present a fast approach for fall recognition. This approach according to human-body skeleton information which was obtained from Kinect sensor. First, following the falls defined by FICSIT, head and center joints, and their relative distance are considered as feature to describe the behavior. Second, applying the slide-window method and threshold for behavior action stage, motion...
Man-machine game is an important component in the field of artificial intelligence. Game tree search algorithms and chess situation evaluation functions are mostly applied in the traditional chess game system. When the game tree method is used, the response time will be extended as the depth of tree. This paper proposes to use the stochastic weight assignment neural network (SWAN), trained by Extreme...
Good features are critical for the research of speech emotion recognition. This paper based on the theory of deep learning, and phonetic features were extracted by using the method of deep auto-encoder (DAE). In this paper, a deep auto-encoder containing five hidden layers was designed. To get the input data, we divided the audio into short frames, each frame of speech emotion signal was then decomposed...
Electroencephalogram (EEG), which is widely used for brain computer interface (BCI) systems for input signal, is easily interrupted by physical or mental tasks, and contaminated with various artifacts including power line noise, electromyogram and electrocardiogram. Therefore, such kind of artifacts cause to decrease the accuracy rate and motivate the researchers substantially develop the performance...
Malware is a computer program or a piece of software that is designed to penetrate and detriment computers without owner's permission. There are different malware types such as viruses, rootkits, keyloggers, worms, trojans, spywares, ransomware, backdoors, bots, logic bomb, etc. Volume, Variant and speed of propagation of malwares are increasing every year. Antivirus companies are receiving thousands...
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