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1.5 Conclusion

Оглавление

This chapter focuses on the processing of several TEMVIs such as EV, ENV, LV, SARS-CoV-2 and ZV using ML-based approach. The TEMVIs are analyzed by applying ML-based classification techniques such as LR, NN, kNN and NB. Each technique carries out the classification mechanism on several TEMVIs. From the analysis of results, it is concluded that the CA values changes for each classification technique when the NoF changes. The maximum CA value is provided by NB technique when the NoF is considered as 20. The NB technique provides overall better classification results as compared to LR, NN and kNN techniques by considering different NoF. This work will be extended to analyze the performance of these ML-based classification techniques along with other classification techniques by focusing on other types of TEMVIs as well as coronavirus dis-ease-19 (COVID-19) images in future.

Machine Vision Inspection Systems, Machine Learning-Based Approaches

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