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Image Enhancement, by P.K. Biswas

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Bayes Decision Theory, by P.K. Biswas

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Lecture 36: CNN Architecture, by P.K. Biswas

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Feature Extraction-III, by P.K. Biswas

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Lecture 59 : Variational Autoencoder-III, by P.K. Biswas

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Lecture 16: Interpolation and Resampling, by P.K. Biswas

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Lecture 51 : Face Recognition, by P.K. Biswas

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Lecture 50 : Colour Image Processing : Colour Fundamentals, by P.K. Biswas

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Lecture 30 : Histogram Equalization and Specifications-I, by P.K. Biswas

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RBF Neural Network, by P.K. Biswas

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Memory Organization-II, by P.K. Biswas

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Lecture 14: Multiclass Support Vector Machine-I, by P.K. Biswas

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Lecture 31: Autoencoder Training, by P.K. Biswas

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Lecture 11: Support Vector Machine-I, by P.K. Biswas

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Neural Networks for Pattern Recognition (Contd.), by P.K. Biswas

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Lecture 23: Basis Images, by P.K. Biswas

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Image Restoration-II, by P.K. Biswas

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Lecture 37: MLP Versus CNN, Popular CNN Architecture: Lenet, by P.K. Biswas

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Feature Extraction-I, by P.K. Biswas

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Lecture 41: Frequency Domain Processing Techniques, by P.K. Biswas

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Secondary Storage Organization-III, by P.K. Biswas

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Mathematical Morphology-IV, by P.K. Biswas

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Lecture 56 : Different Approaches for Image Segmentation, by P.K. Biswas

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Hyperbox Classifier, by P.K. Biswas

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Lecture 46 : Other Restoration Techniques-I, by P.K. Biswas

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Lecture 39 : Image Enhancement : Mask Processing Techniques-II, by P.K. Biswas

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Lecture 46: Normalization, by P.K. Biswas

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Colour Image Processing-II, by P.K. Biswas

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Reflex Fuzzy Min Max Neural Network, by P.K. Biswas

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Lecture 35: Histogram Equalization and Specification-II, by P.K. Biswas

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