AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 641 to 650 of 817 articles

Face Alignment With Deep Regression.

IEEE transactions on neural networks and learning systems Nov 1, 2016
In this paper, we present a deep regression approach for face alignment. The deep regressor is a neural network that consists of a global layer and multistage local layers. The global layer estimates the initial face shape from the whole image, while...
Humans Neural Networks, Computer Machine Learning Image Processing, Computer-Assisted Regression Analysis Facial Expression Biometric Identification Photic Stimulation
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Airline Passenger Profiling Based on Fuzzy Deep Machine Learning.

IEEE transactions on neural networks and learning systems Sep 27, 2016
Passenger profiling plays a vital part of commercial aviation security, but classical methods become very inefficient in handling the rapidly increasing amounts of electronic records. This paper proposes a deep learning approach to passenger profilin...
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Cluster Validation Method for Determining the Number of Clusters in Categorical Sequences.

IEEE transactions on neural networks and learning systems Sep 27, 2016
Cluster validation, which is the process of evaluating the quality of clustering results, plays an important role for practical machine learning systems. Categorical sequences, such as biological sequences in computational biology, have become common...
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Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices.

IEEE transactions on neural networks and learning systems Sep 13, 2016
Data encoded as symmetric positive definite (SPD) matrices frequently arise in many areas of computer vision and machine learning. While these matrices form an open subset of the Euclidean space of symmetric matrices, viewing them through the lens of...
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Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.

IEEE transactions on neural networks and learning systems Jun 24, 2016
In this paper, we have introduced a general modeling approach for dynamic nonlinear systems that utilizes a variant of the simulated annealing algorithm for training the Laguerre-Volterra network (LVN) to overcome the local minima and convergence pro...
Humans Neural Networks, Computer Algorithms Computer Simulation Animals Models, Neurological Action Potentials Neurons Nonlinear Dynamics
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Feature Selection Based on Structured Sparsity: A Comprehensive Study.

IEEE transactions on neural networks and learning systems Apr 22, 2016
Feature selection (FS) is an important component of many pattern recognition tasks. In these tasks, one is often confronted with very high-dimensional data. FS algorithms are designed to identify the relevant feature subset from the original features...
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Learning With Jensen-Tsallis Kernels.

IEEE transactions on neural networks and learning systems Apr 14, 2016
Jensen-type [Jensen-Shannon (JS) and Jensen-Tsallis] kernels were first proposed by Martins et al. (2009). These kernels are based on JS divergences that originated in the information theory. In this paper, we extend the Jensen-type kernels on probab...
Neural Networks, Computer Machine Learning Algorithms Cluster Analysis Probability
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Modeling Disease Progression via Multisource Multitask Learners: A Case Study With Alzheimer's Disease.

IEEE transactions on neural networks and learning systems Feb 24, 2016
Understanding the progression of chronic diseases can empower the sufferers in taking proactive care. To predict the disease status in the future time points, various machine learning approaches have been proposed. However, a few of them jointly cons...
Humans Neural Networks, Computer Machine Learning Algorithms Disease Progression Time Factors Alzheimer Disease Datasets as Topic Linear Models Neuroimaging
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Machine Learning Capabilities of a Simulated Cerebellum.

IEEE transactions on neural networks and learning systems Jan 26, 2016
This paper describes the learning and control capabilities of a biologically constrained bottom-up model of the mammalian cerebellum. Results are presented from six tasks: 1) eyelid conditioning; 2) pendulum balancing; 3) proportional-integral-deriva...
Humans Neural Networks, Computer Machine Learning Computer Simulation Animals Models, Neurological Postural Balance Neurons Cerebellum Reinforcement, Psychology Pattern Recognition, Physiological Conditioning, Eyelid
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Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective.

IEEE transactions on neural networks and learning systems Jan 21, 2016
This paper considers cooperative kinematic control of multiple manipulators using distributed recurrent neural networks and provides a tractable way to extend existing results on individual manipulator control using recurrent neural networks to the s...
Neural Networks, Computer Cooperative Behavior Game Theory
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