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Score normalisation with cohort speaker models has been widely used in HMM-based speaker verification. Most of the proposed methods are based on the framework of the hypothesis testing. Based on this framework an overall average of all cohort scores is often used for normalisation, which leads a log likelihood ratio (LLR) for verification. In this paper we use a competition-based criterion to define...
We propose a new ECG data compression algorithm based on a learned overcomplete dictionary to exploit the correlation between signals in adjacent heart beats. The learned overcomplete dictionary is constructed by K-SVD dictionary learning algorithm, after preprocessing and normalization of length and magnitude. Using the overcomplete dictionary, the proposed algorithm can find sparse estimation, which...
Availability of a single training sample (STS) or degraded set (DS) of training and testing samples restricts the success of face recognition in real-world applications. We propose a unified framework for handling both these challenges simultaneously by using a data dictionary, which is a combination of training dictionary and intra-class variation dictionary. The training dictionary is assembled...
At the current rate of technological advancement and social acceptance thereof, it will not be long before wearable devices will be common that constantly record the field of view of the user. We introduce a new database of image sequences, taken with a first person view camera, of realistic, everyday scenes. As a distinguishing feature, we manually transcribed the scene text of each image. This way,...
In this paper, we propose a new feature learning approach called complete discriminative feature learning (CDFL) for heterogeneous face recognition. Unlike most existing heterogeneous face recognition methods where hand-crafted feature descriptors are used for face representation, the proposed CD-FL aims to learn an optimal weighted discriminative image filter to improve learning discriminative filters,...
This research deals with quantifying the benefits of using the novel Sum Normalized Range Profile (SNRP) over prior art for 1-d feature extraction based classification of maritime vessels. For a fair comparison, classification and feature extraction techniques are maintained the same, for each range profile input. While utilizing SNRP inputs, the automated target recognition engine results indicate...
This paper presents a novel method for pattern recognition problem in terms of linear regression. Normally, patterns from a single-object class lie on a linear subspace. Using this concept, we develop a linear model representing a probe image as a linear combination of class-specific galleries. Linear Regression Classification (LRC) algorithm for pattern recognition belongs to the category of nearest...
We introduce in this paper a concept of using acoustic superframes, a mid-level representation which can overcome the drawbacks of both global and simple frame-level representations for acoustic events. Through superframe-level recognition, we explore the phenomenon of superframe co-occurrence across different event categories and propose an efficient classification scheme that takes advantage of...
SMS messaging is a popular media of communication. Because of its popularity and privacy, it could be used for many illegal purposes. Additionally, since they are part of the day to day life, SMSes can be used as evidence for many legal disputes. Since a cellular phone might be accessible to people close to the owner, it is important to establish the fact that the sender of the message is indeed the...
Though customer databases are so important, they can be sold under 95/46/EC and Data Protection Act law. This is a potential business. However, this business are encountering a big problem that purchaser wants to illegally distribute his database. We call them attacker. Attacker can use many schemes such as attribute, collusion and complimentary attack to achieve his goal. We have improved the technique...
In this paper, we propose voice conversion based on articulatory-movement (AM) to vocal tract parameter (VTP) mapping. An artificial neural network (ANN) is applied to map AM to VTP and to convert the source speaker's voice to the target speaker's voice. The proposed system is not only text independent voice conversion, but can also be used for an arbitrary source speaker. This means that our approach...
In this paper, a computationally efficient approach to transcription of monophonic melodies from a raw acoustic signal is presented. Two different instance-based pitch classification methods are proposed, the choice of which depends on the size of the available training database. In the first method, the conventional K-Nearest Neighbor algorithm is trained on a large database of piano tones and employed...
A review of the published research confirms that recognition of printed Arabic Word continues to present challenges. This is specially the case when segmentation is problematic. A word level recognition system is presented here that does not rely on any segmentation or require baseline detection of ascenders and descenders. A Discrete Hidden Markov classifier along with a block-based Discrete Cosine...
It is still a very challenging task to recognize a face in a real world scenario, since the face may be corrupted by many unknown factors. Among them, illumination variation is an important one, which will be mainly discussed in this paper. First, the illumination variations caused by shadow or overexposure are regarded as a multiplicative scaling image over the original face image. The purpose of...
Although it is valuable information that human faces are approximately symmetric, in the literature of facial attributes recognition, little consideration has been given to the relationship between gender, age, ethnicity, etc. and facial asymmetry. In this paper we present a new approach based on bilateral facial asymmetry for gender classification. For that purpose, we propose to first capture the...
A new approach for static signature verification is presented in this paper. The approach uses optical flow to estimate local stability among signatures. In the enrollment stage, optical flow is used to define a stability model of the genuine signatures for each signer. In the verification stage, the stability between the unknown signature and each one of the reference signatures is estimated and...
In this paper, a technique for the recognition of unconstrained Arabic printed text is proposed. Features that measure the image characteristics at local scales are applied. A line image is divided into a set of one-pixel width windows which is sliding a cross that text line. Run length encoding is used to extract features from each window. A unique method is chosen to select best number of transitions...
Face verification is defined as a person whose identity is claimed a priori will be compared with the person's individual template in database, and then the system checks whether the similarity between pattern and template is sufficient to provide access. In this paper we introduce a new procedure of face verification with an embedding Electoral College framework, which has been applied successfully...
We present a novel approach to fault detection and Physical Asset Health Management (PAHM) called Logical Analysis of Data (LAD). LAD is a supervised learning, artificial intelligence, data mining technique that possesses distinctive advantages which proved to be of use in PAHM. This approach has been introduced by a group of researchers at Rutgers University in the USA, in the medical field, and...
The recent researches in localization technique have been supported by the emerging of wireless sensor network (WSN) technology. The issues of power and time consumption have become the main research topics in WSN-based localization technique. ZigBee as IEEE 802.15.4 is commonly used as supporting device because of its advantages for low-power, small and smart sensor nodes. This paper proposes the...
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