Browsing by Author "Gaikwad, Sushant Suresh"

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    Active Dataset Adaptation Based Covid-19 Detection via Deep learning Techniques
    (Department of Computer Science & Engineering, NITS, 2022) Gaikwad, Sushant Suresh
    An epidemic of Covid-19 disease resulting from the 2019 novel coronavirus started in Wuhan, China, at the end of 2019 and has outspread worldwide. Till now many Covid-19 detection models using Deep learning models has and these models are giving promising lab results but most of them are trained and tested On same Of data only, but when it to real world scenarios, these models are overfitting and give less accuracy because of image parameter differences in lab images and real world images. This work mainly deals with resolving the overfitting problem generated after testing the model on new image data. A single or homogeneous dataset with different sources is used for the experiment, which has somewhat similar images but belongs from different sources. In initial experimental results, the base CNN model gives 70.06 % training and 64.23 % validation accuracy. Whereas VGG 16, training and validation accuracy is better than base CNN with 81.54 %, and 75.62 % respectively. Finally the Resnet50 model giving training and validation accuracy is somewhat improved than VGG16 and much more improved than base CNN with 90.23 %, and 85.56 % respectively. These models are used for testing new images from a different source. On new data, the CNN has a accuracy of 55.23 VGG16 has a test accuracy of 68.34 and Resnet50 has a test accuracy of 77.32 Vo. To overcome the overfitting problem on new image data, all models are again with new data images using an active learning approach. The Least confidence technique is to calculate uncertain images to retrain. After active learning training with three cycles, it is found that test accuracy is somewhat increased on new data for all models but not increased to previously trained data accuracy. The new test accuracy for CNN, VGG16, and Resnet50 arc 60.53, 71.94, and 80.65, respectively. Resnet50 is giving the best in all cases among all implemented models.