Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mobile Freeze-Net with Attention-based Loss Function for Covid-19 Detection from an Imbalanced CXR Dataset Subject The topic of the resource attention-based loss function; chest X-ray (CXR) images; class imbalance; Covid-19 detection; mobile freeze-net Description An account of the resource In this paper, we present a novel framework, that is, Mobile Freeze-Net along with Attention-based Loss Function, for Covid-19 detection from a Chest X-Ray (CXR) dataset. First, we have observed that by freezing 50% of a Mobile Net-V2 model (means fine-tuning 50% layers from ImageNet dataset) has automatically removed the class imbalance problem from the CXR dataset considerably. We call this 50% frozen Mobile Net-V2 model as Mobile Freeze-Net. Secondly, we have proposed an Attention-based Loss function, which provides more attention to the class, having higher inter-class similarity. We have computed attention weights for each class from the statistical inference of the dataset itself, by employing a Monte-Carlo method and thereafter, we have incorporated those weights into WCCE loss function of Mobile Freeze-Net model. By utilizing Mobile freeze-Net, we have achieved testing accuracy, F1 score, precision and recall of 93%, 94%, 93% and 94% respectively. This is approximately 3-4% improvement compared to 100% fine tuning of Mobile-Net V2. Furthermore, we have achieved approximate 1-2% improvement of Mobile Freeze-Net, after incorporating Attention-based Loss function. For the validity of the proposed framework, we have conducted experiments with 10-fold cross validation. All these experimental results suggest that our proposed framework has outperformed other existing models considerably. 2023 Owner/Author(s). Creator An entity primarily responsible for making the resource Roy S.; Khurana R. Source A related resource from which the described resource is derived Proceedings of the ACM Symposium on Applied Computing, pp. 611-613. Publisher An entity responsible for making the resource available Association for Computing Machinery Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1145/3555776.3577825" target="_blank" rel="noreferrer noopener">https://doi.org/10.1145/3555776.3577825</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162901128&amp;doi=10.1145%2F3555776.3577825&amp;partnerID=40&amp;md5=44bc5f929758cc88a9c62a1e60e45497" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162901128&amp;doi=10.1145%2f3555776.3577825&amp;partnerID=40&amp;md5=44bc5f929758cc88a9c62a1e60e45497</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-145039517-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Roy S., Christ (Deemed to Be University), Bangalore, India; Khurana R., Bharati Vidyapeeth's College of Engineering, New Delhi, India