Skip to main content

Research Repository

Advanced Search

All Outputs (4)

Topology for preserving feature correlation in tabular synthetic data. (2022)
Conference Proceeding
ARIFEEN, M. and PETROVSKI, A. 2022. Topology for preserving feature correlation in tabular synthetic data. In Proceedings of the 15th IEEE (Institute of Electrical and Electronics Engineers) International conference on security of information and networks 2022 (SINCONF 2022), 11-13 November 2022, Sousse, Tunisia. Piscataway: IEEE [online], pages 61-66. Available from: https://doi.org/10.1109/SIN56466.2022.9970505

Tabular synthetic data generating models based on Generative Adversarial Network (GAN) show significant contributions to enhancing the performance of deep learning models by providing a sufficient amount of training data. However, the existing GAN-ba... Read More about Topology for preserving feature correlation in tabular synthetic data..

Deep learning models for the diagnosis and screening of COVID-19: a systematic review. (2022)
Journal Article
SIDDIQUI, S., ARIFEEN, M.A., HOPGOOD, A., GOOD, A., GEGOV, A., HOSSAIN, E., RAHMAN, W., HOSSAIN, S., AL JANNAT, S., FERDOUS, R. and MASUM, S. 2022. Deep learning models for the diagnosis and screening of COVID-19: a systematic review. SN computer science [online], 3(5), article 397. Available from: https://doi.org/10.1007/s42979-022-01326-3

COVID-19, caused by SARS-CoV-2, has been declared as a global pandemic by WHO. Early diagnosis of COVID-19 patients may reduce the impact of coronavirus using modern computational methods like deep learning. Various deep learning models based on CT a... Read More about Deep learning models for the diagnosis and screening of COVID-19: a systematic review..

Autoencoder based consensus mechanism for blockchain-enabled industrial Internet of Things. (2022)
Journal Article
ARIFEEN, M., GHOSH, T., ISLAM, R., ASHIQUZZAMAN, A., YOON, J. and KIM, J. 2022. Autoencoder based consensus mechanism for blockchain-enabled industrial Internet of Things. Internet of things [online], 19, article 100575. Available from: https://doi.org/10.1016/j.iot.2022.100575

Conventional blockchain technologies developed for cryptocurrency applications involve complex consensus algorithms which are not suitable for resource constrained Internet of Things (IoT) devices. Therefore, several lightweight consensus mechanisms... Read More about Autoencoder based consensus mechanism for blockchain-enabled industrial Internet of Things..

A comparative study of deep-learning models for COVID-19 diagnosis based on X-ray images. (2022)
Book Chapter
SIDDIQUI, S., HOSSAIN, E., FERDOUS, R., ARIFEEN, M., RAHMAN, W., MASUM, S., HOPGOOD, A., GOOD, A. and GEGOV, A. 2022. A comparative study of deep-learning models for COVID-19 diagnosis based on X-ray images. In Howlett, R.J., Jain, L.C., Littlewood, J.R. and Balas, M.M. (eds.) Smart and sustainable technology for resilient cities and communities. Singapore: Springer [online], pages 163-174. Available from: https://doi.org/10.1007/978-981-16-9101-0_12

Background: The rise of COVID-19 has caused immeasurable loss to public health globally. The world has faced a severe shortage of the gold standard testing kit known as reverse transcription-polymerase chain reaction (RT-PCR). The accuracy of RT-PCR... Read More about A comparative study of deep-learning models for COVID-19 diagnosis based on X-ray images..