Search results for: Loo Chu Kiong
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In this paper, a deep-learning based architecture is proposed to estimate gender which includes both supervised and unsupervised facial feature extraction techniques and a deep network to fuse features and to classify them. As unsupervised techniques we have benefited deep-learning feature extraction method called convolutional neural network, and for supervised facial feature extraction we have used...
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Multiple sensor data fusion is the technique of associate information from a number of different sensors to produce a robust and comprehensive description. Data fusion pose is using in various robotics application such as environment mapping, object recognition and robot localization. Their relation is generally hard coded and difficult to learn incrementally if new objects or events arise. In this...
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Neural Computing and Applications > 2017 > 28 > 1 > 461-474
In multi-agent system (MAS) applications, teamwork among the agents is essential as the agents are required to collaborate and pool resources to execute the given tasks and complete the objectives successfully. A vital part of the collaboration is sharing of information and resources in order to optimize their efforts in achieving the given objectives. Under such collaborative environment, trust among...
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This paper describes an evidence-theoretic classifier which employs global k-means algorithm as the clustering method. The classifier is based on the Dempster-Shafer rule of evidence in the form of Basic Belief Assignment (BBA). This theory combines the evidence obtained from the reference patterns to yield a new BBA. Global k-means is selected as the clustering algorithm as it can overcomes the limitation...
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In this study, we aim to develop a system for improving daily lives of elderly people to ensure health. In order to realize an enriched life style among elderly people, daily health care is important. Therefore, we have proposed a system where robot partners will assist in exercising activity among elderly people. This paper proposes a method of relational trust modeling based on reinforcement learning...
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If a robot partner can provide a multimodal interaction with a person, it may offer more smooth and natural human-robot communication. This paper proposes a method for modeling relationship between behavioral and emotional expression through human-robot interaction. First, we applied a neuro-fuzzy system to the classification of human posture. Next, we used the facial expression recognition algorithms...
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Simultaneous localization and mapping (SLAM) is an important system for making fully autonomous robot navigation system. A robot must have a good understanding of the environment for navigation. Mobile robot using fixed laser range finder can only detect obstacle on a particular plane level. This may lead to missing of important obstacles that are both above or below the laser scan level. This will...
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Recurrent neural networks (RNN) are powerful sequence learners. However, RNN suffers from the problem of vanishing gradient point. This fact makes learning sequential task more than 10 time steps harder for RNN. Recurrent network with LSTM cells as hidden layers (LSTM-RNN) is a deep learning recurrent network architecture designed to address the vanishing gradient problem by incorporating memory cells...
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Recent works involved in enhancing the learning convergence of reinforcement learning (RL) in mobile robot navigation have investigated methods to obtain knowledge from efficiently exploring the robot's environment. In RL, this knowledge is highly desirable to reduce the high number of interactions required for updating the value function and to eventually find an optimal or suboptimal policy for...
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Speech is structured acoustic signals which form a message featuring the speaker's language, speaking style, and also underlying emotion. These features affect the information passed through speech. Automated speech emotion recognition is a field long studied, but it has not yet found a quite reliable approach. This paper explores two ways to improve automated recognition. First, new sets or combinations...
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Discriminant Common Vectors (DCV) is proposed to solve small sample size problem. Face recognition encounters this dilemma where number of training samples is always smaller than the data dimension. In literature, it is shown that DCV is efficient in face recognition. In this paper, DCV is enhanced for further boosting its discriminating power. This modified version is namely Discriminative Discriminant...
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Arabian Journal for Science and Engineering > 2013 > 38 > 8 > 2219-2226
This paper presents an emitted sound signal analysis technique for tool flank wear monitoring based on the Hilbert–Huang Transform (HHT). HHT is a new signal processing technique suitable for analyzing non-stationary and non-linear signals like emitted sound. The need for HHT in this analysis and its principle are explained. The entire experiment was done on a conventional turning machine using carbide...
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A small change in image will cause a dramatic change in signals. Visual system needs to ignore these changes, yet specific enough to perform recognition. Problem intended to be solved is on 2D translation and scaling invariances and 3D pose invariance without imposing strain on memory and with biological justification. In this paper, we propose a novel biologically inspired vision model for pose-invariant...
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Journal of Bodywork & Movement Therapies > 2011 > 15 > 4 > 453-464
A method for assessing balance, which was sensitive to changes in the postural control system is presented. This paper describes the implementation of a force-sensing platform, with force sensing resistors as the sensing element. The platform is capable of measuring destabilized postural perturbations in dynamic and static postural conditions. Besides providing real-time qualitative assessment, the...
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Applied Soft Computing > 2011 > 11 > 1 > 1117-1125
A fuzzy model based on enhanced supervised fuzzy clustering algorithm is presented in this paper. Supervised fuzzy clustering algorithm by Janos Abonyi and Ferenc Szeifert in the year 2003 allows each rule to represent more than one output with different probabilities for each output. This algorithm implements k-means to initialize the fuzzy model. The main drawbacks of this approach are the number...
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The ability of human brain in making decisions based on the available information stored in the memory and the information provided through cognitive process are the motivations of simulating human intelligence. This paper presents a brain model able to recognize biological behavioral patterns of human locomotion using synergetic approach. Two human-like motion patterns are studied here: slow and...
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A two-factor face authentication method is presented by using topographic independent component analysis (TICA) as feature extractor in conjunction with multi space random projection (MRP). Instead of using face alone to access the system, a permissible access requires a pair of genuine face and valid token in authentication mechanism. The formulation is revocable but not reversible and makes replacement...
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A hybrid system of case based reasoning (CBR) with fuzzy ARTMAP (FAM) has been proposed to perform fault diagnosis for actuator system in DAMADICS benchmark. The hybrid system of CBR and FAM is for undertaking the stability plasticity dilemma for the incremental learning problem in CBR. At the same time, FAM can overcome the difficulty of indexing and retrieval in CBR as well as adaption of cases...
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A great interest for brain machine interface (BMI) is in the arising nowadays, instigated by several promising scientific and technological outcomes. The methods of measuring, processing and classifying brain activities, in order to interpret neuronal signals into machine control is often regarded as a challenging possibility as the expected beneficiaries are patients affected by motor disorders and...
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The development of an artificial visual system consists of several algorithms based on the biological human eye sight, particularly about the retina. It involves algorithms such as log polar transformation, Gaussian filters, Gabor Wavelets, etc. Overall, the system is implemented into recognition and able to perform some tracking abilities.
