All Outputs (4)

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..

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..

A next-generation telemedicine and health advice system. (2021)
Presentation / Conference Contribution
SIDDIQUI, S., HOPGOOD, A., GOOD, A., GEGOV, A., HOSSAIN, E., RAHMAN, W., FERDOUS, R., ARIFEEN, M. and KHAN, Z. 2021. A next-generation telemedicine and health advice system. In Yang, X.-S., Sherratt, S., Dey, N. and Joshi, A. (eds.) Proceedings of sixth International congress on information and communication technology, 25-26 February 2021, London, UK. Lecture notes in networks and systems, 236. Singapore: Springer [online], pages 981-989. Available from: https://doi.org/10.1007/978-981-16-2380-6_87

This project aims to create a real-time health advice platform andtelemedicine system that can reach healthcare providers and healthcare deprived people. A pragmatic approach is being used to understand the research problem of this study, which allow... Read More about A next-generation telemedicine and health advice system..

Performance analysis of different loss function in face detection architectures. (2020)
Presentation / Conference Contribution
FERDOUS, R.H., ARIFEEN, M.M., EIKO, T.S. and AL MAMUN, S. 2020. Performance analysis of different loss function in face detection architectures. In Kaiser, M.S., Bandyopadhyay, A., Muhmad, M. and Ray, K. (eds.) Proceedings of International conference on trends in computational and cognitive engineering 2020 (TCCE-2020), 17-18 December 2020, Dhaka, Bangladesh. Singapore: Springer [online], 659-669. Available from: https://doi.org/10.1007/978-981-33-4673-4_54

Masked face detection is a challenging task due to the occlusions created by the masks. Recent studies show that deep learning models can achieve effective performance for not only occluded faces but also for unconstrained environments, illuminations... Read More about Performance analysis of different loss function in face detection architectures..