Proceedings ArticleDOI
Radon transform processed neural network for lung X-ray image based diagnosis
Chethan Sharma,Shafeena Basheer,Anish Francis,V. Jayakrishna +3 more
- pp 1-4
TLDR
A novel method for image diagnosis with artificial learning is presented-ray images tuberculosis patients is subjected to neural network learning for prediction of diagnosis, distincting the normal and abnormal images.Abstract:
A novel method for image diagnosis with artificial learning is presented-ray images tuberculosis patients is subjected to neural network learning for prediction of diagnosis. The X-ray images of lungs are normally difficult for diagnosis, since its similarity to lung cancer. Under and over diagnosis of lung X-ray images is a difficult medical problem to resolve. In the present work radon transform of the x-ray images is fed to back propagation neural network trained with Levenberg algorithm. The present methodology gives sharp results, distincting the normal and abnormal images.read more
Citations
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Proceedings ArticleDOI
Comparison of Feature Extraction Methods and Deep Learning Framework for Depth Map Recognition
TL;DR: It is shown that the Convolutional Neural Network based deep learning framework achieve better classification performance than test feature extraction methods (Fourier Transform, Radon Transform, Canny Edge Filter).
Proceedings ArticleDOI
WeLDCFNet: Convolutional Neural Network based on Wedgelet Filters and Learnt Deep Correlation Features for depth maps features extraction
TL;DR: WeLDCFNet as discussed by the authors proposes an automatic depth maps features extraction model based on an optimized Convolutional Neural Network (CNN), trained on a mixture of depth maps and grayscale texture images.
References
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Proceedings ArticleDOI
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