Convolution Neural Network for Image Processing of Friction Stir Welded and Conventional Welded Joints Texture
Keywords:
Convolution Neural Network, Friction Stir Welding, Image Processing, Deep LearningAbstract
Image processing becomes powerful if deep learning algorithms like Convolution Neural Networks are used. This research paper deals with the classification of types of welding into Conventional welding and Friction stir Welding. Friction Stir Welding (FSW) method is an innovative solid-state welding technique used for joining the alloys which are difficult to weld. We tried implementing a convolution neural network that can classify them.
References
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2. Karunanithi, N., Whitley, D. and Malaiya, Y.K., 1992. Using neural networks in reliability prediction. IEEE Software, 9(4), pp.53-59.
3. Hijazi, S., Kumar, R. and Rowen, C., 2015. Using convolutional neural networks for image recognition. Cadence Design Systems Inc.: San Jose, CA, USA.
4. Chen, X., Weng, J., Lu, W., Xu, J. and Weng, J., 2017. Deep manifold learning combined with convolutional neural networks for action recognition. IEEE transactions on neural networks and learning systems, 29(9), pp.3938-3952.
2. Karunanithi, N., Whitley, D. and Malaiya, Y.K., 1992. Using neural networks in reliability prediction. IEEE Software, 9(4), pp.53-59.
3. Hijazi, S., Kumar, R. and Rowen, C., 2015. Using convolutional neural networks for image recognition. Cadence Design Systems Inc.: San Jose, CA, USA.
4. Chen, X., Weng, J., Lu, W., Xu, J. and Weng, J., 2017. Deep manifold learning combined with convolutional neural networks for action recognition. IEEE transactions on neural networks and learning systems, 29(9), pp.3938-3952.
Published
2019-07-01
Issue
Section
Articles
