Emotions are caused by a human brain reaction to objective events. The purpose of this study is to investigate emotion identification by machine learning using electroencephalography (EEG) data.

Indoor localization is an essential part of many applications of the Internet of Things, and to track an object within a building with the required precision and reliability one needs to give ...

The dataset used was a widely known credit card fraud detection benchmark obtained from Kaggle. It is notoriously imbalanced, with only 0.172% of the transactions being fraudulent. To mitigate this, ...

During training, however, I encountered some issues. Specifically, I observed that the autoencoder failed to converge. I applied normalization and added noise to the raw data, yet the MSE decreased ...

This project modifies the classic VGG16 architecture to classify images into four distinct categories with high accuracy. It incorporates data augmentation, dynamic learning rate adjustments, and ...