Projects

In this project, the P300 event occurred due to the shift in attention is analyzed and captured using the electroencephalogram (EEG). Using this analysis, a model called Cortically-Coupled Generative Adversarial Network is developed. This model identifies and retrieves the target image in a rapid serial visual presentation(RSVP) event

Machine anomaly detection for Multivariate Time Series

In this project, I have used a technique to detect anomaly in a complex system made by multiple correlated series. I have used the LSTM model to extract features from the correlated series of sensor data. The sensor data is first denoised, and then the relationship among the features is learned with dimensionality reduction. The learned relationship is them used to build an automated mechanism to alert the times of fault and failure in the machine.

Product description classification using NER

In this project, the product is classified by performing entity recognition from product descriptio using NER. The laptops data was scrapped from the eBay website using Beautifulsoup. Entities are the laptop description (Product Brand, Product Model, Hard disk type/size, display type, etc.) available on the eBay site.