2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA) 2017
DOI: 10.1109/iccubea.2017.8463867
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Performance Evaluation of Object Detection Algorithm Using Ant Colony Optimization Based Image Segmentation

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Cited by 5 publications
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“…The marker 'g' has a place with best particles among occupants and V_m1,V_m2… … ..V_(md )Represents the different speeds of the particles. Condition (1) portrays the speed modification over the procedure and condition (2) shows the refreshing of position for each fly molecule. On the off chance that the estimation of V_(md )is more noteworthy than the client particular limit Vmax this outcomes into the progressively modification of Vmax esteem Figure 2 Standard flowchart of PSO The steps used are specified below:…”
Section: Particle Swarm Optimizationmentioning
confidence: 99%
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“…The marker 'g' has a place with best particles among occupants and V_m1,V_m2… … ..V_(md )Represents the different speeds of the particles. Condition (1) portrays the speed modification over the procedure and condition (2) shows the refreshing of position for each fly molecule. On the off chance that the estimation of V_(md )is more noteworthy than the client particular limit Vmax this outcomes into the progressively modification of Vmax esteem Figure 2 Standard flowchart of PSO The steps used are specified below:…”
Section: Particle Swarm Optimizationmentioning
confidence: 99%
“…This deprivation arises in many forms such as action haze, noise or if the camera is unable to focus. In cases of degradation which deals with the moving parts, it is feasible to move toward the high-quality estimation of the parameters which leads to removal of this blur/ haze effect in order to achieve the better quality [2]. There are certain cases where the quality of an image is reduced due to the presence of noise.…”
Section: Introductionmentioning
confidence: 99%