DenoiseNet is a powerful image processing project that utilizes a convolutional autoencoder to effectively remove noise from images, enhancing their quality and visual appeal. This project focuses on ...

Abstract: Non-parallel many-to-many voice conversion remains an interesting but challenging speech processing task. Recently, AutoVC, a conditional autoencoder based method, achieved excellent ...

This project is a personal practice attempt at performing anomaly detection on a multivariate time-series dataset. The dataset chosen is the Tennessee Eastman dataset, and anomalies in the data are ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

Abstract: Class imbalance occurs in many real-world applications, including image classification, where the number of images in each class differs significantly. With imbalanced data, the generative ...

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