Browsing by Author "Verma, R."

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    Automatic Abnormality Detection in Musculoskeletal Radiographs Using Ensemble of Pre-trained Networks
    (Springer Science and Business Media Deutschland GmbH, 2023) Verma, R.; Jain, S.; Saritha, S.K.; Dodia, S.
    Musculoskeletal disability (MSDs) defined as the injuries that affect the movement or musculoskeletal system of the human body. Over the worldwide, it is the second most cause of physical disability. Musculoskeletal disability worsens over time and can result in long-term discomfort and severe disability. As a result, early detection and diagnosis of these anomalies is essential. But the diagnosis process is very time consuming, error prone and required diagnostic professional. Deep learning algorithms have recently been applied in medical imaging that provides a robust platform with very reliable outcomes. The development of Computer Aided Detection (CAD) system extensively speed up the diagnosis process. In this paper, a weighted ensemble model has been proposed, which is the combination of three pre-trained models (DenseNet169, MobileNet, and XceptionNet). The weighted ensemble model is tested on MURA dataset, a large public dataset provided by Stanford ML Group. Our model achieved a cohen’s kappa score 0.739 with precision of 0.885 and recall of 0.854, which is higher than many existing approaches such as densenet169 and ensemble200 model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Urban Weighted Green Index- A study of urban green space in relation to Land Surface Temperature for Lucknow city, India
    (Elsevier B.V., 2020) Verma, R.; Kundapura, S.
    It is of substantial importance, that the green spaces with regards to the urban areas are quantified in a manner that a planned urban area is developed and utilized with best access to vegetation. There exist various factors which affect built-up areas and corresponding neighbourhood like Vegetation Density (VD), Proximity to high vegetation areas (VDP), Built-up Density (BD), Rise of built-up (HT), and Proximity to high built-up density (BDP). In this study using ©JAXA AW3D DSM and above mentioned factors, Urban Weighted Green Index (UWGI) is generated. To understand the UHI effect, Land Surface Temperature (LST) is generated using radiative transfer equation, which is used for portraying relationship between LST and UWGI for 33 zones and different land use (LU) and land cover (LC) classes of Lucknow Development Authority area. Interdependent effect of all factors was compared and it is seen that VD and VP to different rise areas is affecting areas more than RD and RP, in terms of UWGI and LST both. The increase of one unit in UWGI is affecting the decrease of 2.5 ?C in various LU classes of Lucknow city. © 2020 Elsevier B.V.