Deep Learning Transfer: COVID-19 CT-scan Classification Insights

Abstract:

COVID-19 has become a pandemic for the entire world, and it has significantly affected the world economy. The importance of early detection and treatment of the infection cannot be overstated. The traditional diagnosis techniques take more time in detecting the infection. Although, numerous deep learning-based automated solutions have recently been developed in this regard, nevertheless, the limitation of computational and battery power in resource-constrained devices makes it difficult to deploy trained models for real-time inference. In this paper, to detect the presence of COVID-19 in CT-scan images, an important weights-only transfer learning method has been proposed for devices with limited runt-time resources. In the proposed method, the pre-trained models are made point-of-care devices friendly by pruning less important weight parameters of the model. The experiments were performed on two popular VGG16 and ResNet34 models and the empirical results showed that pruned ResNet34 model achieved 95.47% accuracy, 0.9216 sensitivity, 0.9567 F-score, and 0.9942 specificity with 41.96% fewer FLOPs and 20.64% fewer weight parameters on the SARS-CoV-2 CT-scan dataset. The results of our experiments showed that the proposed method significantly reduces the run-time resource requirements of the computationally intensive models and makes them ready to be utilized on the point-of-care devices.

Publication: Applied Intelligence

Publisher: Springer Nature

Authors: Tejalal Choudhary, Shubham Gujar, Anurag Goswami and Tapas Badal

Keywords: Convolutional neural network, Deep learning, Pruning, COVID-19, Automated diagnosis

Meet one of the Author:

Dr Tejalal Choudhary received his Ph.D. in Computer Science Engineering from Bennett University in Greater Noida, India. He has expertise in computer vision, machine learning, deep learning, and model compression. His exceptional ability to think creatively, tackle problems from multiple angles, and generate innovative solutions sets him apart from others.

Affiliations:

Bennett University, Greater Noida, India – Bennett University was established in the year 2016 by the Times Group which is India’s largest media conglomerate, to provide Ivy League quality education to undergraduate and postgraduate students. The six schools with 30+ programs and 70+ leading specialisations in Engineering, Management, Media, Law and Liberal Arts have positioned it as one of the top universities in India.

Vishwakarma Institute of Information Technology – The Vishwakarma Institute of Information Technology is an autonomous institute of engineering in Pune, India. Established in 2002, it is affiliated to the Savitribai Phule Pune University. The college is run by the Bansilal Ramanath Agarwal Charitable Trust.