Rahul Sankar - Academia.edu (original) (raw)

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Papers by Rahul Sankar

Research paper thumbnail of MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray Images

The world is going through a challenging phase due to the disastrous effect caused by the COVID-1... more The world is going through a challenging phase due to the disastrous effect caused by the COVID-19 pandemic on the healthcare system and the economy. The rate of spreading, post-COVID-19 symptoms, and the occurrence of new strands of COVID-19 have put the healthcare systems in disruption across the globe. Due to this, the task of accurately screening COVID-19 cases has become of utmost priority. Since the virus infects the respiratory system, Chest X-Ray is an imaging modality that is adopted extensively for the initial screening. We have performed a comprehensive study that uses CXR images to identify COVID-19 cases and realized the necessity of having a more generalizable model. We utilize MobileNetV2 architecture as the feature extractor and integrate it into Capsule Networks to construct a fully automated and lightweight model termed as MobileCaps. MobileCaps is trained and evaluated on the publicly available dataset with the model ensembling and Bayesian optimization strategies...

Research paper thumbnail of MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray Images

ArXiv, 2021

The world is going through a challenging phase due to the disastrous effect caused by the COVID-1... more The world is going through a challenging phase due to the disastrous effect caused by the COVID-19 pandemic on the healthcare system and the economy. The rate of spreading, re-infections, post-COVID-19 symptoms, and the occurrence of new strands of COVID-19 have put the healthcare systems in disruption across the globe. Due to this, the task of accurately screening COVID-19 cases has become of utmost priority. Since the virus infects the respiratory system, Chest X-Ray (CXR) is an imaging modality that is adopted extensively for the initial screening. We have performed a comprehensive study that uses CXR images to identify COVID-19 cases and realized the necessity of having a more generalizable model. We utilize MobileNetV2 architecture as the feature extractor and integrate it into Capsule Networks to construct a fully automated, hybrid, and lightweight model termed as MobileCaps. MobileCaps is trained and evaluated on the publicly available COVIDx dataset with the model ensembling...

Research paper thumbnail of Capsule Network–based architectures for the segmentation of sub-retinal serous fluid in optical coherence tomography images of central serous chorioretinopathy

Medical & Biological Engineering & Computing

Research paper thumbnail of MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray Images

The world is going through a challenging phase due to the disastrous effect caused by the COVID-1... more The world is going through a challenging phase due to the disastrous effect caused by the COVID-19 pandemic on the healthcare system and the economy. The rate of spreading, post-COVID-19 symptoms, and the occurrence of new strands of COVID-19 have put the healthcare systems in disruption across the globe. Due to this, the task of accurately screening COVID-19 cases has become of utmost priority. Since the virus infects the respiratory system, Chest X-Ray is an imaging modality that is adopted extensively for the initial screening. We have performed a comprehensive study that uses CXR images to identify COVID-19 cases and realized the necessity of having a more generalizable model. We utilize MobileNetV2 architecture as the feature extractor and integrate it into Capsule Networks to construct a fully automated and lightweight model termed as MobileCaps. MobileCaps is trained and evaluated on the publicly available dataset with the model ensembling and Bayesian optimization strategies...

Research paper thumbnail of MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray Images

ArXiv, 2021

The world is going through a challenging phase due to the disastrous effect caused by the COVID-1... more The world is going through a challenging phase due to the disastrous effect caused by the COVID-19 pandemic on the healthcare system and the economy. The rate of spreading, re-infections, post-COVID-19 symptoms, and the occurrence of new strands of COVID-19 have put the healthcare systems in disruption across the globe. Due to this, the task of accurately screening COVID-19 cases has become of utmost priority. Since the virus infects the respiratory system, Chest X-Ray (CXR) is an imaging modality that is adopted extensively for the initial screening. We have performed a comprehensive study that uses CXR images to identify COVID-19 cases and realized the necessity of having a more generalizable model. We utilize MobileNetV2 architecture as the feature extractor and integrate it into Capsule Networks to construct a fully automated, hybrid, and lightweight model termed as MobileCaps. MobileCaps is trained and evaluated on the publicly available COVIDx dataset with the model ensembling...

Research paper thumbnail of Capsule Network–based architectures for the segmentation of sub-retinal serous fluid in optical coherence tomography images of central serous chorioretinopathy

Medical & Biological Engineering & Computing

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