Journal ArticleDOI
A connectionist model for category perception: theory and implementation
TLDR
A connectionist model for learning and recognizing objects (or object classes) is presented and the theory of learning is developed based on some probabilistic measures.Abstract:Â
A connectionist model for learning and recognizing objects (or object classes) is presented. The learning and recognition system uses confidence values for the presence of a feature. The network can recognize multiple objects simultaneously when the corresponding overlapped feature train is presented at the input. An error function is defined, and it is minimized for obtaining the optimal set of object classes. The model is capable of learning each individual object in the supervised mode. The theory of learning is developed based on some probabilistic measures. Experimental results are presented. The model can be applied for the detection of multiple objects occluding each other. >read more
Citations
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Journal ArticleDOI
Cellular neural network architecture for Gibbs random-field-based image segmentation
Chang Wen Chen,Lulin Chen +1 more
TL;DR: A novel cellular connectionist neural network model for the implementation of clustering-based Bayesian image segmentation with Gibbs random-field spatial constraints is described and it is proved that this cellular neural network does converge to the desired steady state with a properly designed update scheme.
Journal ArticleDOI
A cellular neural network for clustering-based adaptive quantization in subband video compression
TL;DR: It is proved that the proposed cellular neural network does converge to the desired steady state with the proposed, update scheme, and provides a general architecture for image processing tasks with Gibbs spatial constraint-based computations.
Journal ArticleDOI
Joint Scene and Signal Modeling for Wavelet-Based VideoCoding with Cellular Neural Network Architecture
TL;DR: This paper presents a joint scene and signal modeling for the design of an adaptive quantization scheme applied to the wavelet coefficients in subband video coding applications and proves that this cellular neural network does converge to the desired steady state with the suggested update scheme.
Journal ArticleDOI
A self-organizing network for mixed category perception
TL;DR: A neural network model capable of self-organizing in presence of multiple or mixed categories is presented and a certainty factor is derived about the decision on how well the features have been interpreted by the network.
Proceedings ArticleDOI
ART2-Based Approach to Judge the State of the Blast Furnace
TL;DR: When a batch of new data is collected, the state of the blast furnace can be predicated by the ART2 neural network and achieves high veracity.
References
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