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M. Sultan Zia

Researcher at University of Lahore

Publications -  14
Citations -  407

M. Sultan Zia is an academic researcher from University of Lahore. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 5, co-authored 8 publications receiving 130 citations.

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Sixth generation (6G)wireless networks: Vision, research activities, challenges and potential solutions

TL;DR: This study highlights the most promising lines of research from the recent literature in common directions for the 6G project, exploring the critical issues and key potential features of 6G communications and contributing significantly to opening new horizons for future research directions.
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State-of-the-Art CNN Optimizer for Brain Tumor Segmentation in Magnetic Resonance Images.

TL;DR: A comparative analysis of 10 different state-of-the-art gradient descent-based optimizers of CNN, namely Adaptive Gradient (Adagrad), Adaptive Delta (AdaDelta), Stochastic Gradient Descent (SGD),adaptive Momentum (Adam), Cyclic Learning Rate (CLR), Adaptives Max Pooling (Adamax), Root Mean Square Propagation (RMS Prop), Nesterov AdaptiveMomentum (Nadam),
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Texture based localization of a brain tumor from MR-images by using a machine learning approach.

TL;DR: The multi-modal brain images dataset (BraTs 2012) was used and achieves the dice overlap score of 88% for the whole tumour area localization, which is similar to the declared score in MICCAI BraTS challenge.
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Survey: smartphone-based assessment of cardiovascular diseases using ECG and PPG analysis.

TL;DR: A categorical review of smartphone-based systems that can detect cardiac abnormalities by the analysis of Electrocardiogram and Photoplethysmography and the limitation and challenges of these system are presented.
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A secure demand response management authentication scheme for smart grid

TL;DR: Wang et al. as mentioned in this paper proposed an anonymous and lightweight authenticated key agreement protocol for smart grid-based demand response management countering the limitations in Yu et al.'s scheme, and proved the security of session key between the utility center and smart grid using Burrows Abadi Needham (BAN) logic analysis and ProVerif automated simulation.