All Outputs (10)

Enhancing brain tumor classification with transfer learning across multiple classes: an in-depth analysis. (2023)
Journal Article
AHMMED, S., PODDER, P., MONDAL, M.R.H., RAHMAN, S.M.A., KANNAN, S., HASAN, M.J., ROHAN, A. and PROSVIRIN, A.E. 2023. Enhancing brain tumor classification with transfer learning across multiple classes: an in-depth analysis. Biomedinformatics [online], 3(4), pages 1124-1144. Available from: https://doi.org/10.3390/biomedinformatics3040068

This study focuses on leveraging data-driven techniques to diagnose brain tumors through magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we introduce and fine-tune two robust frameworks, ResNet 50 and Inception V3,... Read More about Enhancing brain tumor classification with transfer learning across multiple classes: an in-depth analysis..

Rethinking densely connected convolutional networks for diagnosing infectious diseases. (2023)
Journal Article
PODDER, P., ALAM, F.B., MONDAL, M.R.H., HASAN, M.J., ROHAN, A. and BHARATI, S. 2023. Rethinking densely connected convolutional networks for diagnosing infectious diseases. Computers [online], 12(5), article 95. Available from: https://doi.org/10.3390/computers12050095

Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a valuable and cost-effective tool for detecting and diagnosing COVID-19 patients. I... Read More about Rethinking densely connected convolutional networks for diagnosing infectious diseases..

Deep scattering spectrum germaneness for fault detection and diagnosis for component-level prognostics and health management (PHM). (2022)
Journal Article
ROHAN, A. 2022. Deep scattering spectrum germaneness for fault detection and diagnosis for component-level prognostics and health management (PHM). Sensors [online], 22(23), article 9064. Available from: https://doi.org/10.3390/s22239064

Most methodologies for fault detection and diagnosis in prognostics and health management (PHM) systems use machine learning (ML) or deep learning (DL), in which either some features are extracted beforehand (in the case of typical ML approaches) or... Read More about Deep scattering spectrum germaneness for fault detection and diagnosis for component-level prognostics and health management (PHM)..

Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM). (2022)
Journal Article
ROHAN, A. 2022 Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM). Mathematics [online], 10(12), article number 2031. Available from: https://doi.org/10.3390/math10122031

In the current Industry 4.0 revolution, prognostics and health management (PHM) is an emerging field of research. The difficulty of obtaining data from electromechanical systems in an industrial setting increases proportionally with the scale and acc... Read More about Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM)..

Rotate vector (Rv) reducer fault detection and diagnosis system: towards component level prognostics and health management (phm). (2020)
Journal Article
ROHAN, A., RAOUF, I. and KIM, H.S. 2020. Rotate vector (Rv) reducer fault detection and diagnosis system: towards component level prognostics and health management (phm). Sensors [online], 20(23), article 6845. Available from: https://doi.org/10.3390/s20236845

In prognostics and health management (PHM), the majority of fault detection and diagnosis is performed by adopting segregated methodology, where electrical faults are detected using motor current signature analysis (MCSA), while mechanical faults are... Read More about Rotate vector (Rv) reducer fault detection and diagnosis system: towards component level prognostics and health management (phm)..

Human pose estimation-based real-time gait analysis using convolutional neural network. (2020)
Journal Article
ROHAN, A., RABAH, M., HOSNY, T. and KIM, S.-H. 2020. Human pose estimation-based real-time gait analysis using convolutional neural network. IEEE access [online] 8, pages 191542-191550. Available from: https://doi.org/10.1109/ACCESS.2020.3030086

Gait analysis is widely used in clinical practice to help in understanding the gait abnormalities and its association with a certain underlying medical condition for better diagnosis and prognosis. Several technologies embedded in the specialized dev... Read More about Human pose estimation-based real-time gait analysis using convolutional neural network..

Heterogeneous parallelization for object detection and tracking in UAVs. (2020)
Journal Article
RABAH, M., ROHAN, A., HAGHBAYAN, M.-H., PLOSILA, J. and KIM, S.-H. 2020. Heterogeneous parallelization for object detection and tracking in UAVs. IEEE access [online], 8, pages 42784-42793. Available from: https://doi.org/10.1109/ACCESS.2020.2977120

Recent technical advancements in both fields of unmanned aerial vehicles (UAV) control and artificial intelligence (AI) have made a certain realm of applications possible. However, one of the main problems in integration of these two areas is the bot... Read More about Heterogeneous parallelization for object detection and tracking in UAVs..

Convolutional neural network-based real-time object detection and tracking for parrot AR drone 2. (2019)
Journal Article
ROHAN, A., RABAH, M. and KIM, S.-H. 2019. Convolutional neural network-based real-time object detection and tracking for parrot AR drone 2. IEEE access [online], 7, pages 69575-69584. Available from: https://doi.org/10.1109/ACCESS.2019.2919332

Recent advancements in the field of Artificial Intelligence (AI) have provided an opportunity to create autonomous devices, robots, and machines characterized particularly with the ability to make decisions and perform tasks without human mediation.... Read More about Convolutional neural network-based real-time object detection and tracking for parrot AR drone 2..

Autonomous moving target-tracking for a UAV quadcopter based on fuzzy-PI. (2019)
Journal Article
RABAH, M., ROHAN, A., MOHAMED, S.A.S. and KIM, S.-H. 2019. Autonomous moving target-tracking for a UAV quadcopter based on fuzzy-PI. IEEE access [online] 7, pages 38407-38419. Available from: https://doi.org/10.1109/ACCESS.2019.2906345

Moving target-tracking is an attractive application for quadcopters and a very challenging, complicated field of research due to the complex dynamics of a quadcopter and the varying speed of the moving target with time. For this reason, various contr... Read More about Autonomous moving target-tracking for a UAV quadcopter based on fuzzy-PI..

Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm. (2018)
Journal Article
ROHAN, A., RABAH, M., TALHA, M. and KIM, S.-H. 2018. Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm. Applied system innovation [online], 1(4), article 44. Available from: https://doi.org/10.3390/asi1040044

In this work, an advanced drone battery charging system is developed. The system is composed of a drone charging station with multiple power transmitters and a receiver to charge the battery of a drone. A resonance inductive coupling-based wireless p... Read More about Development of intelligent drone battery charging system based on wireless power transmission using hill climbing algorithm..