Abstract
Artificial intelligence (AI) has been able to solve the problems effectively in our day-to-day life in today’s world. Year 2020 has seen worldwide pandemic COVID-19 which has thrown normal life out of gear. Social distancing and sanitization are new norms of life. Robot with AI techniques will help to solve the problems associated with it. This paper highlights use of deep learning-based techniques to predict the disease. It takes a lot of time in lab almost 2–3 days to diagnose the covid patients with the help of gold-standard real-time reverse transcription polymerase chain reaction (rRT-PCR). Another major diagnostic tool is radio imaging; however, with the help of artificial intelligence (AI)-based deep learning methods, it is much easier to diagnose the disease. Computer vision is a scientific field that deals with how computers can be made to gain high-level understanding of the real world from digital images or videos. In terms of engineering, it seeks to automate tasks that the human vision system can do. This paper is based on one specific task in computer vision called as image segmentation. Even though researchers have come up with various methods to solve this problem, in this work it will be working with architecture named U-NET a type of encoder-decoder network along with ResNet-34.
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Jain, R., Singh, S., Swami, S., kumar, S. (2021). Deep Learning-Based Techniques to Identify COVID-19 Patients Using Medical Image Segmentation. In: Manocha, A.K., Jain, S., Singh, M., Paul, S. (eds) Computational Intelligence in Healthcare. Health Information Science. Springer, Cham. https://doi.org/10.1007/978-3-030-68723-6_18
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