Discussions

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An Automated Teeth Lesion Diagnosis based on Deep Learning Techniques

A pipeline based on context-aware light-weight transformers with the goal of improving image quality without sacrificing the naturalness of the image, as well as reducing the inference time and size of the model. In this study, we trained a deep network-based transformer model on two standard datasets, i.e., Large-Scale Underwater Image (LSUI) and Underwater Image Enhancement Benchmark Dataset (UIEB), so that the network becomes more generalized, which subsequently improved the performance. Our real-time underwater image enhancement system shows superior results on edge devices. Also, we provide a comparison with other transformer-based methods.

Using Vision Transfers for Image Enhancement

A pipeline based on context-aware light-weight transformers with the goal of improving image quality without sacrificing the naturalness of the image, as well as reducing the inference time and size of the model. In this study, we trained a deep network-based transformer model on two standard datasets, i.e., Large-Scale Underwater Image (LSUI) and Underwater Image Enhancement Benchmark Dataset (UIEB), so that the network becomes more generalized, which subsequently improved the performance. Our real-time underwater image enhancement system shows superior results on edge devices. Also, we provide a comparison with other transformer-based methods.

Editorial Activities

Editor Journals Organizing and Publication Chair of International Conferences: Member Program Committee and Reviewer of International Conferences: Reviewer of International Journals (with Impact Factors) IEEE Elsevier Springer ACM Hindawi & Wiley Others Reviewer of Local Journals (HEC Recognized)

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Khawir Mahmood

Assistant Professor at NUST Pakistan. His Interests are: Machine Learning, Large Language Models

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Dr. Asim Dilawar Bakhshi

Dr. Asim Bakhshi has been teaching at NUST as an Associate Professor since Sep, 2020. His research interests include Large Language Models, Application of ML in Signal Processing.​​

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Socio-economic and Geographical factors for Crime Incidents

Spatio-temporal data mining techniques are used for crime analysis for their knowledge oriented and meaningful visual representation of crime incidents. Visual representation of crime patterns assist analysts with in-depth understanding of crime behavior with time and location. The representation can be made more knowledgeable and perceptible by incorporating details of socio-economic factor and areafis geographical […]