Federated Learning (FL) is a collaborative learning platform. It enables users to train machine learning models on their devices using their data. However, the final updated model they receive is trained on other datasets ...

Approximate Computing has emerged as a promising solution to address the increas ing computational demands of modern applications by allowing controlled inaccu racies. This thesis explores the integration of Approximate ...

The acoustic classification of ships at sea is a crucial factor for the monitoring of maritime activities and safeguarding navigation safety in the maritime environment. To utilize the advanced AI-powered methodologies ...

Remote sensing (RS) datasets have gained popularity due to their impact on addressing global issues such as food security and climate change. The crop type data availability is valuable for agronomy managers to address ...

Law enforcement agencies (LEAs) face the persistent challenge of rapidly detecting suspicious vehicles fleeing from CCTV surveillance streams. While current machine learning (ML) and deep learning (DL) models are valuable ...

E-learning has been a common option for students during epidemic scenarios. Modern research relies heavily on software systems because they help scientists solve challeng ing problems, analyse enormous volumes of data, ...

Big data has become a ubiquitous feature of modern society, providing opportunities for extracting valuable insights from large datasets. However, the sheer volume, variety, and complexity of big data make it difficult to ...