The purpose of this study is to investigate a novel end-to-end deep learning method of emotion recognition using EEG data, which prefaces a combination of two-dimensional (2D) convolutional network ...

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, ...

I experimented with different numbers of steps, learning rates, and modified the convolution kernel sizes, channel counts, and the model_dim in the autoencoder. Despite testing various combinations, I ...

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 ...