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The idea of lip reading as a visual technique which people may use to translate lip movement into phrases without relying on speech itself is fascinating. There are numerous application areas in which lip reading could provide full assistance. Although there may be a downside to using the lip reading system, whether it may range from problems such as time constraint to minor word recognition mistakes,...
This paper proposes an effective fusion scheme for extracting more discriminative information from bimodal biometrics at data, feature and decision levels. In all these three levels of fusion, information from both face andfingerprint image of a single subject are fused to effectively represent it in a more discriminative ways. For all these three approaches, a combination of wavelet and principal...
This work aims to present a system for automatic music mood classification based on acoustic and visual features extracted from the music. The visual features are obtained from spectrograms and the acoustic features are extracted directly from the audio signal. The texture operators used are Local Phase Quantization (LPQ), Local Binary Pattern (LBP) and Robust Local Binary Pattern (RLBP). The acoustic...
Patients who are conscious and aware of their environment but are physically disabled are known to have Locked-in Syndrome. The causes for this medical condition include traffic accidents, drug addiction and brain clots. There are some available solutions nowadays to help them communicate but the down side is the requirement for physical training which can be both time and money consuming. The main...
Grey Level Co-Occurrence matrix is one of the oldest techniques used for texture analysis. The Grey Level Co-Occurrence matrix has two important parameters i.e. distance and direction. In this paper various combinations of distance and directional angles used for GLCM calculation are analyzed in order to recognize certain patterned images based on their textural features. Patterns considered in this...
This paper presents the design of a convolutional neural network architecture using the MatConvNet library for MATLAB in order to achieve the recognition of 2 classes of hand gestures: ”open” and ”closed”. Six architectures were implemented to which their hyperparameters and depth were varied to observe their behavior through the validation error in the training and accuracy in the estimation of each...
Most existing hashing methods resort to binary codes for similarity search, owing to the high efficiency of computation and storage. However, binary codes lack enough capability in similarity preservation, resulting in less desirable performance. To address this issue, we propose an asymmetric multi-valued hashing method supported by two different non-binary embeddings. (1) A real-valued embedding...
Palm vein recognition is developing biometric identification technology. It can be used in physical security and information security for selective control of access to a place or resource. A palm vein recognition has been gaining research interest from last few years because it use physiological intrinsic that uniqueness, stability, not easily spoofed and damaged and have live body identification...
Music emotions recognition (MER) is a challenging field of studies addressed in multiple disciplines such as musicology, cognitive science, physiology, psychology, arts and affective computing. In this paper, music emotions are classified into four types known as those of pleasing, angry, sad and relaxing. MER is formulated as a classification problem in cognitive computing where 548 dimensions of...
Palm vein recognition is a new biometric identification technology. The horizontal rotation, translation, tilting and loss of local vein information of palm vein image greatly affect recognition rate. To solve the above problems, this paper respectively extract four kinds of local invariant feature, Scale Invariant Feature Transform(SIFT), Affine-SIFT(ASIFT), Harris-Laplace and Maximally Stable Extremal...
The past decade has witnessed the popularity of video conferencing, such as FaceTime and Skype. In video conferencing, almost every frame has a human face. Hence, it is necessary to predict attention on face videos by saliency detection, as saliency can be used as a guidance of regionof- interest (ROI) for the content-based applications. To this end, this paper proposes a novel approach for saliency...
This paper presents a framework for real-time contingency screening using a situational awareness oriented tool. While some contingencies might have a significant impact on power-system stability, the impact of others is negligible. The consequences of a contingency depend on network conditions. Therefore, fast and effective tools for rapid recognition of hazardous operating conditions from the stability...
This paper addresses the problem of Approximate Nearest Neighbor (ANN) search in pattern recognition where feature vectors in a database are encoded as compact codes in order to speed-up the similarity search in large-scale databases. Considering the ANN problem from an information-theoretic perspective, we interpret it as an encoding, which maps the original feature vectors to a less entropic sparse...
A novel RRAM-based pattern recognition system with locally inhibited post-neurons is developed. The system is able to learn the whole MNIST training set (60,000 patterns). By using the system, the same post-neuron is fired by the similar patterns in the same training class, which causes the reduction of hardware cost. With the locally inhibited post-neuron, the system can achieve more than 90.73%...
In this paper we propose a new post-processing approach for dimensionality reduction methods based on multidimensional ensemble empirical mode decomposition (MEEMD). In the proposed method, the features are decomposed into different components and then we maximize the dependency and the dispersion between classes thanks to Gaussian filter and Butterworth filter. The performance of the proposed algorithm...
In this study, pattern recognition based brain computer interface is designed using EEG p300 component elicited by visual stimuli. A novel EEG database obtained from 19 subjects is constructed with EMOTIV EPOC+ amplifier and OPENVIBE software. Extreme Learning Machine, a type of single layer neural network, Λ-nearest neighbour, Bayesian network and Multi-Layer Perceptron classifiers are compared for...
By passing of time, the size of data such as fMRI scans, speech signals and digital photographs becomes very high and it takes large amount of time for data processing. To overcome this problem, the dimensionality of data should be reduced. Whereas graph embedding introduces a successful framework for dimensionality reduction, we use it as the base of our proposed method. In this framework, similarity...
This paper presents a novel landmark based audio fingerprinting algorithm for matching naval vessels' acoustic signatures. The algorithm incorporates joint time - frequency based approach with parameters optimized for application to acoustic signatures of naval vessels. The technique exploits the relative time difference between neighboring frequency onsets, which is found to remain consistent in...
A large corpus of ceramic sherds dating from High Middle Ages has been extracted in Saran (France). The sherds have an engraved frieze made by the potter with a carved wooden wheel, used as a dating to study the dissemination of productions. ARCADIA project aims to develop an automatic classification of this archaeological heritage. The sherds are scanned using a 3D laser scanner. Then, a binary pattern...
In the context of tree species recognition, botanists knowledge was used in different works specially when recognising tree species through leaves. In this paper, two sub-classification strategies for tree species recognition are proposed. For each sub-classification strategy, Basic belief assignment (Bba) was determined and obtained data were fused thanks to a totally adaptive fusion system implemented...
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