Identification and Localization of COVID-19 Abnormalities on Chest Radiographs using Ensembled Deep Neural Networks

With the hit of the global pandemic COVID-19, the chest X-ray domain has gained prominence. It has been recognised as one of the principal methods to learn the presence of infection and its effect on various internal organs like the lungs. Chest radiographs show abnormalities due to COVID-19 that appear similar to the anomalies caused by other viruses and bacteria, thus making it challenging for technicians to detect. Therefore, it becomes almost inevitable to have a computer vision model that identifies and localizes the COVID-19 virus to help doctors provide an immediate and confident diagnosis. The models in computer vision tasks have seen considerable advancements in deep learning, so the proposed model tried to integrate a few of them to come up with a model for classifying and localising the diagnosis of COVID-19 using chest X-rays. This paper ensembles a few state-of-the-art models in classification and object detection to build a model for chest radiograph diagnosis. The proposed ensembled model is found to achieve the mean Average Precision value of 0.627 on SIIM-FISABIO-RSNA COVID-19 dataset. © 2022 IEEE.

Managing sustainable transitions: Institutional innovations from india

Despite the widespread disruptions of lives and livelihoods due to the COVID-19 pandemic, it could also be seen as a gamechanger. The post-pandemic recovery should address fundamental questions concerning our food systems. Is it possible to reset existing ecologically unsustainable production systems towards healthier and more connected systems of conscious consumers and ecologically oriented farmers? Based on three illustrative cases from different parts of India, we show how managing transitions towards sustainability require institutional innovations and new intermediaries that build agency, change relations, and transform structures in food systems. Lessons from three diverse geographies and commodities in India are presented: Urban farming initiatives in Mumbai, conscious consumer initiatives in semi-urban Gujarat for pesticide-free mangoes, and resource-poor arid regions of Andhra Pradesh. Through these examples, we show that, beyond the technological solutions, institutional innovations such as urban community-supported farming models, Participatory Guarantee Schemes, and Farmer Producer Organisations (FPOs) can enable sustainable transitions. Sustainable lifestyles in a post COVID-19 world, as the cases show, require collective experimentation with producers that go beyond changed consumer behaviour to transform structures in food systems. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.