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Through this paper, we examine the impact of telemedicine among patients and healthcare professionals during the second wave of COVID-19 pandemic in India. Using the electronic and communication technologies, telemedicine is used to transfer the information from one place to another place. The foremost utility peculiar to telemedicine is to render assistance in medical aid by referring to Information and Communication Technology (ICT). It is not safe to visit a hospital physically even in extreme emergency during a second wave of pandemic. Henceforth, telemedicine plays an important role in this situation. Use of telemedicine during a pandemic helps to improve the quality of health services and improve access to the various medicinal facilities to the people that are not easily available. We have been told the importance of using telehealth to provide us healthcare in the present scenario, specifically as a means of reducing the risk of cross contamination caused by contact. Like other countries, India also began providing digital healthcare services as means of telemedicine during the outbreak of the second wave of COVID-19 pandemic. With the increase in the surge of the second wave of COVID-19 pandemic, many telemedicine service providers in India have also expanded their service operations for the general public. In this paper, a survey is being presented based on the e-sanjeevani data regarding the continuous increase of the impact of telemedicine during the spread of the second wave of COVID-19. After performing the latest literature surveys on many papers, we analyzed the consequences of telemedicine since the inception of first wave of COVID-19 pandemic till the surge of second wave. After discussions and analysis, we conclude that the use of telemedicine continuously expands during the second wave of COVID-19. In spite of numerous issues and challenges in the domain of a telemedicine sector in India, continuous improvements have been made for its survival and existence even in the rural, background and isolated areas. [ABSTRACT FROM AUTHOR]

Image processing domain involves various steps like preprocessing, augmentation, segmentation and recognition of images. Consistent image segmentation technique plays crucial role in computer vision domain. Using sophisticated segmentation techniques or segmentation models on image datasets resolves recognition, detection, feature extraction and classification issues in image processing and computer vision problems. Several literature surveys have shown improvement in the results after applying these segmentation techniques in the domain of machine learning as well as in deep learning. In this paper, we are analyzing mainly wheat leaf diseases by applying segmentation techniques or segmentation models in both machine learning and deep learning areas. We are also reviewing various segmentation techniques applied on other crops for comparative analysis with the wheat crops. [ABSTRACT FROM AUTHOR]

Timely analysis and recognition of leaf diseases in plants ensures good quality and productivity of crops in the field of agriculture. Recognition of rice leaf diseases is one of the biggest challenges for the farmers due to incomplete awareness regarding latest sophisticated techniques in the field of leaf disease identification. Much of the growth of rice is disturbed due to the prevalence of rice leaf diseases. Earlier detection of rice leaf diseases done manually by farmers which is very laborious and time consuming. However, requisite of automatic identification of rice leaf diseases helps farmers to save their agricultural crops more efficiently. Innovations in the field of computer vision and deep learning meets the expectations and proves to be the best solution for classification of rice leaf diseases using convolutional neural networks using samples of rice leaf diseases. In this review paper, the major focus is on performance analysis of detection of rice leaf diseases based on the architectures employed. [ABSTRACT FROM AUTHOR]