Improvement of Video Human Activity Recognization by using ANN Approach

6,000.00

Improvement of Video Human Activity Recognization by using ANN Approach

100 in stock

SKU: Improvement of Video Human Activity Recognization Category:

Description

Improvement of Video Human Activity Recognization by using ANN Approach

In this project,is human activity recognization by using ANN approach.Watershed segmentation technique is used in this project. Artificial Neural Networks can be best viewed as weighted directed graphs, where the nodes are formed by the artificial neurons and the connection between the neuron outputs and neuron inputs can be represented by the directed edges with weights.HSV color area was found to convey higher results compared to the RGB color area, in our experiments the RGB and HSV color areas were found to convey virtually equivalent results. K-MEAN primarily bunch rule has been projected and also the iterations taken was abundant less than that of K-MEAN and ANN based schemes. Moreover, K-MEAN based mostly schemes might discover all the peaks and categories accurately. The impact of the configuration, migration policy, rate of migration, and kind of migration on the speed convergence has been studied and it had been discovered that the migration policy and rate of migration greatly influence the convergence rate.

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