Decision analysis : a Bayesian approach
Decision analysis : a Bayesian approach
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
A particle filter for joint detection and tracking of color objects
Image and Vision Computing
Letters: Convex incremental extreme learning machine
Neurocomputing
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
OP-ELM: optimally pruned extreme learning machine
IEEE Transactions on Neural Networks
Underwater image processing: state of the art of restoration and image enhancement methods
EURASIP Journal on Advances in Signal Processing - Special issue on advances in signal processing for maritime applications
Learning capability and storage capacity of two-hidden-layer feedforward networks
IEEE Transactions on Neural Networks
Universal approximation using incremental constructive feedforward networks with random hidden nodes
IEEE Transactions on Neural Networks
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In this paper, we present one dynamic model hypothesis to perform fish trajectory tracking in the fish ethology research and develop the relevant mathematical criterion on the basis of the Extreme Learning Machine (ELM). It is shown that the proposed scheme can conduct the non-linear and non Gaussian tracking process by multiple historical cues and current predictions - the state vector motion, the color distribution and the appearance recognition, all of which can be extracted from the single-hidden layer feedforward neural network (SLFN) at diverse levels with ELM. The strategy of the hierarchical hybrid ELM ensemble then combines the individual SLFN of the tracking cues for the performance improvements. The simulation results have shown the excellent performance in both robustness and accuracy of the developed approach.