This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The pre-processed image is segmented using the hybrid geneticArtificial Bee Colony(ABC) algorithm that is developed by hybridizing the ABC and ge...

This paper presents a new approach based on HMM/ANN hybrid for online signature verification. The hybrid HMM/ANN model is constructed by using a type of time delay Neural Networks as local probability estimators for an HMM, where a posterior probability of the model is worked out by the Viterbi algorithm, given an observation sequence. The proposed HMM/ANN hybrid has a strong discriminant abili...

-The findings of recent studies are showing strong evidence to the fact that some aspects of biogeography can be applied to solve specific problems in science and engineering. The proposed work presents a hybrid biologically inspired technique that can be adapted according to the database of expert knowledge for a more focused satellite image classification. The paper also presents a comparativ...

In this paper, we introduce a new restricted Bayesian network classifier that extends naive Bayes by relaxing the conditional independence assumptions, and show that it is partly generative and partly discriminative. Experimental results show that the hybrid classifier performs better than a purely generative classifier (naive Bayes) or a purely discriminative classifier (Logistic Regression) a...

A resource limited immune approach (RLIA) was developed to evolve architecture and initial connection weights of multilayer neural networks. Then, with Back-Propagation (BP) algorithm, the appropriate connection weights can be found. The RLIA-BP classifier, which is derived from hybrid algorithm mentioned above, is demonstrated on SPOT multi-spectral image data, vowel data and Iris data effecti...

This paper reports on a two-fold contribution; first, the introduction of a new compaction algorithm for the rules generated by learning classifier systems that overcomes the disadvantages of previous algorithms in complexity, compacted solution size, accuracy and usability. The second is the new hybrid architecture that integrates learning classifier systems with Rete-based Inference Engines t...