Outputs (49)

An Adaptive Xception Model for Classification of Brain Tumors (2024)
Journal Article
Thakur, A., Mahesh, T. R., Khan, S. B., Palaiahnakote, S., Kumar V, V., Vinoth Kumar, V., …Mashat, A. (in press). An Adaptive Xception Model for Classification of Brain Tumors. International Journal of Pattern Recognition and Artificial Intelligence, https://doi.org/10.1142/s0218001424560056

Classification of different brain tumors is challenging due to unpredictable variations in intra-inter-classes. Unlike existing methods which are not effective for images of complex backgrounds, the proposed work aims at accurate classification of di... Read More about An Adaptive Xception Model for Classification of Brain Tumors.

Intelligent Recognition of Multimodal Human Activities for Personal Healthcare (2024)
Journal Article
Sannasi Chakravarthy, S. R., Bharanidharan, N., Vinoth Kumar, V., Mahesh, T. R., Khan, S. B., Almusharraf, A., & Albalawi, E. (2024). Intelligent Recognition of Multimodal Human Activities for Personal Healthcare. IEEE Access, 1-1. https://doi.org/10.1109/access.2024.3405471

Nowadays, the advancements of wearable consumer devices have become a predominant role in healthcare gadgets. There is always a demand to obtain robust recognition of heterogeneous human activities in complicated IoT environments. The knowledge att... Read More about Intelligent Recognition of Multimodal Human Activities for Personal Healthcare.

Enhancing brain tumor classification in MRI scans with a multi-layer customized convolutional neural network approach (2024)
Journal Article
Albalawi, E., Thakur, A., Dorai, D. R., Khan, S. B., Mahesh, T. R., Almusharraf, A., …Anwar, M. S. (in press). Enhancing brain tumor classification in MRI scans with a multi-layer customized convolutional neural network approach. Frontiers in Computational Neuroscience, 18, 1418546. https://doi.org/10.3389/fncom.2024.1418546

Background: The necessity of prompt and accurate brain tumor diagnosis is unquestionable for optimizing treatment strategies and patient prognoses. Traditional reliance on Magnetic Resonance Imaging (MRI) analysis, contingent upon expert interpretati... Read More about Enhancing brain tumor classification in MRI scans with a multi-layer customized convolutional neural network approach.

Few-Shot Learning for Medical Image Segmentation Using 3D U-Net and Model-Agnostic Meta-Learning (MAML) (2024)
Journal Article
Alsaleh, A. M., Albalawi, E., Algosaibi, A., Albakheet, S. S., & Khan, S. B. (in press). Few-Shot Learning for Medical Image Segmentation Using 3D U-Net and Model-Agnostic Meta-Learning (MAML). Diagnostics, 14(12), 1213. https://doi.org/10.3390/diagnostics14121213

Deep learning has attained state-of-the-art results in general image segmentation problems; however, it requires a substantial number of annotated images to achieve the desired outcomes. In the medical field, the availability of annotated images is o... Read More about Few-Shot Learning for Medical Image Segmentation Using 3D U-Net and Model-Agnostic Meta-Learning (MAML).

Refining neural network algorithms for accurate brain tumor classification in MRI imagery (2024)
Journal Article
Alshuhail, A., Thakur, A., Chandramma, R., Mahesh, T. R., Almusharraf, A., Vinoth Kumar, V., & Khan, S. B. (in press). Refining neural network algorithms for accurate brain tumor classification in MRI imagery. BMC Medical Imaging, 24(1), 118. https://doi.org/10.1186/s12880-024-01285-6

Brain tumor diagnosis using MRI scans poses significant challenges due to the complex nature of tumor appearances and variations. Traditional methods often require extensive manual intervention and are prone to human error, leading to misdiagnosis an... Read More about Refining neural network algorithms for accurate brain tumor classification in MRI imagery.

Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol (2024)
Journal Article
Khan, S. B., Kumar, A., Mashat, A., Pruthviraja, D., Imam Rahmani, M. K., & Mathew, J. (in press). Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol. SN Computer Science, 5(5), 546. https://doi.org/10.1007/s42979-024-02778-5

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless se... Read More about Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol.

Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor (2024)
Journal Article
Albalawi, E., T.R., M., Thakur, A., Kumar, V. V., Gupta, M., Khan, S. B., & Almusharraf, A. (in press). Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor. BMC Medical Imaging, 24(1), 110. https://doi.org/10.1186/s12880-024-01261-0

Brain tumor classification using MRI images is a crucial yet challenging task in medical imaging. Accurate diagnosis is vital for effective treatment planning but is often hindered by the complex nature of tumor morphology and variations in imaging.... Read More about Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor.

Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework (2024)
Journal Article
Ahmed, S. T., Mahesh, T. R., Srividhya, E., Vinoth Kumar, V., Khan, S. B., Albuali, A., & Almusharraf, A. (in press). Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework. BMC Medical Imaging, 24(1), 105. https://doi.org/10.1186/s12880-024-01279-4

Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and computational layers, poses a formidable challe... Read More about Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework.

Advancing solar energy integration: Unveiling XAI insights for enhanced power system management and sustainable future (2024)
Journal Article
Nallakaruppan, M., Shankar, N., Bhuvanagiri, P. B., Padmanaban, S., & Bhatia Khan, S. (2024). Advancing solar energy integration: Unveiling XAI insights for enhanced power system management and sustainable future. Ain Shams Engineering Journal ASEJ / Ain Shams University, 15(6), 102740. https://doi.org/10.1016/j.asej.2024.102740

Solar energy has emerged as a vital renewable alternative to fossil fuels, enhancing environmental sustainability in response to the pressing need to reduce carbon emissions. However, the integration of solar power into the electric... Read More about Advancing solar energy integration: Unveiling XAI insights for enhanced power system management and sustainable future.

Decoupled SculptorGAN Framework for 3D Reconstruction and Enhanced Segmentation of Kidney Tumors in CT Images (2024)
Journal Article
Suman Prakash, P., Kiran Rao, P., Suresh Babu, E., Khan, S. B., Almusharraf, A., & Quasim, M. T. (2024). Decoupled SculptorGAN Framework for 3D Reconstruction and Enhanced Segmentation of Kidney Tumors in CT Images. IEEE Access, 1-1. https://doi.org/10.1109/access.2024.3389504

Our proposed work, SculptorGAN, represents a novel advancement in the domain of medical imaging, for the accurate and automatic diagnosis of renal tumors, using the techniques and principles of Generative Adversarial Network (GAN). This dichotomous f... Read More about Decoupled SculptorGAN Framework for 3D Reconstruction and Enhanced Segmentation of Kidney Tumors in CT Images.