Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
Browse
2 results
Search Results
Item COVID-19 Prediction Using Chest X-rays Images(Institute of Electrical and Electronics Engineers Inc., 2021) Kumar, A.; Sharma, N.; Naik, D.Understanding covid-19 became very important since large scale vaccination of this was not possible. Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Till now in various fields, great success has been achieved using convolutional neural networks(CNNs) for image recognition and classification. However, due to the limited availability of annotated medical images, the classification of medical images remains the biggest challenge in medical diagnosis. The proposed research work has performed transfer learning using deep learning models like Resnet50 and VGG16 and compare their performance with a newly developed CNN based model. Resnet50 and VGG16 are state of the art models and have been used extensively. A comparative analysis with them will give us an idea of how good our model is. Also, this research work develops a CNN model as it is expected to perform really good on image classification related problems. The proposed research work has used kaggle radiography dataset for training, validating and testing. Moreover, this research work has used another x-ray images dataset which have been created from two different sources. The result shows that the CNN model developed by us outperforms VGG16 and Resnet50 model. © 2021 IEEE.Item COVID-19 Social Distancing Detection and Email Violation Mechanisms(Springer Science and Business Media Deutschland GmbH, 2023) Bhojak, D.; Jat, T.; Naik, D.The technique of flattening the curve for coronavirus-infected cases is challenging in addressing the worldwide ongoing rampant novel COVID-19 pandemic crisis unless citizens take steps to halt the virus’s spread. Maintaining a safe space between individuals around us in public is one of the most important behaviors. Deep learning algorithms have been used in the proposed work to mitigate the spreading of the coronavirus utilizing social distance detection. This proposed work analyzes a pre-recorded video feed of walking pedestrians to alert people to maintain a safe distance. The goal is achieved using YOLOv3 and YOLOv4 for object detection in the video frame used as input. Furthermore, an email-based alert mechanism is also implemented if the number of violations exceeds the defined limit. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.