20 research outputs found
Weighted PCA for improving Document Image Retrieval System based on keyword spotting accuracy
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A hybrid algorithm for preserving energy and delay routing in mobile ad-hoc networks
No full textThe Quality of Service (QoS) routing protocol plays a vital role in enabling a
mobile network to interconnect wired networks with the QoS support. It has become quite
a challenge in mobile networks, like mobile ad-hoc networks, to identify a path that fulfils
the QoS requirements, regarding their topology and applications. The QoS routing feature
can also function in a stand-alone multi hop mobile network for real-time applications. The
chief aim of the QoS aware protocol is to find a route from the source to the destination that
fulfils the QoS requirements. In this paper we present a new energy and delay aware
routing method which combines Cellular automata (CA) with the Genetic algorithm (GA).
Here, two QoS parameters are used for routing; energy and delay. The routing algorithm
based on CA is used to identify a set of routes that can fulfill the delay constraints and then
select a reasonably good one using GAs. The results of Simulation show that the method
proposed produces a higher degree of performance than the AODV and another QoS
method in terms of network lifetime and end-to-end delay
A new approach to improve load balancing for increasing fault tolerance and decreasing energy consumption in cloud computing
No full textA method for handwritten word spotting based on particle swarm optimisation and multi‐layer perceptron
No full textProviding a method to reduce the false alarm rate in network intrusion detection systems using the multilayer perceptron technique and backpropagation algorithm
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A Novel Word-Spotting Method for Handwritten Documents Using an Optimization-Based Classifier
No full textWord spotting is the answer to the question whether the document contains the user’s query word. One of the main challenges of keyword spotting at the testing stage is that some testing non-classes are not included in training classes. Hence, this paper presents a robust handwritten word-spotting method for handwritten documents using genetic programming (GP). Using this technique, a tree is created as a classifier which separates the target class (keyword) from the other classes (non-keyword). The new components of the proposed classifier include proper chromosome and new classification fitness function. The proposed chromosome was based on the relationship between features and each chromosome (tree) mapped the features to a real number. Then, a margin was obtained from the real number. To evaluate the generality of the proposed method, several experiments have been designed and implemented on three standard datasets (namely IFN/ENIT Arabic for Arabic, IFN/Farsi for Persian, and George Washington for English). The results of experiments carried out on these three datasets show that the proposed method has much higher precision and recall than previous method
Statistical geometric components of straight lines (SGCSL) feature extraction method for offline Arabic/Persian handwritten words recognition
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