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 Articles Article Faculty Publications -Articles 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 Detection and Classification of Colorectal Polyp Using Deep Learning Description An account of the resource Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required to save the life of patients. Cancer grows from polyps which can be either cancerous or noncancerous. So, if the cancerous polyps are detected accurately and removed on time, then the dangerous consequences of cancer can be reduced to a large extent. The colonoscopy is used to detect the presence of colorectal polyps. However, manual examinations performed by experts are prone to various errors. Therefore, some researchers have utilized machine and deep learning-based models to automate the diagnosis process. However, existing models suffer from overfitting and gradient vanishing problems. To overcome these problems, a convolutional neural network- (CNN-) based deep learning model is proposed. Initially, guided image filter and dynamic histogram equalization approaches are used to filter and enhance the colonoscopy images. Thereafter, Single Shot MultiBox Detector (SSD) is used to efficiently detect and classify colorectal polyps from colonoscopy images. Finally, fully connected layers with dropouts are used to classify the polyp classes. Extensive experimental results on benchmark dataset show that the proposed model achieves significantly better results than the competitive models. The proposed model can detect and classify colorectal polyps from the colonoscopy images with 92% accuracy. 2022 Sushama Tanwar et al. Creator An entity primarily responsible for making the resource Tanwar S.; Vijayalakshmi S.; Sabharwal M.; Kaur M.; Alzubi A.A.; Lee H.-N. Source A related resource from which the described resource is derived BioMed Research International, Vol-2022 Publisher An entity responsible for making the resource available Hindawi Limited Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1155/2022/2805607" target="_blank" rel="noreferrer noopener">https://doi.org/10.1155/2022/2805607</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128802566&amp;doi=10.1155%2F2022%2F2805607&amp;partnerID=40&amp;md5=1a782f1a4b7dafdef8ec8b29a227fab1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128802566&amp;doi=10.1155%2f2022%2f2805607&amp;partnerID=40&amp;md5=1a782f1a4b7dafdef8ec8b29a227fab1</a> Rights Information about rights held in and over the resource All Open Access; Green Open Access; Hybrid Gold Open Access Relation A related resource ISSN: 23146133; PubMed ID: 35463989 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 Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tanwar S., Galgotias University, Uttar Pradesh, 201307, India; Vijayalakshmi S., Christ University, Lavasa, 412112, India; Sabharwal M., Galgotias University, Uttar Pradesh, 201307, India; Kaur M., Gwangju Institute of Science and Technology, School of Electrical Engineering and Computer Science, Gwangju, 61005, South Korea; Alzubi A.A., Computer Science Department, Community College, King Saud University, Riyadh, Saudi Arabia; Lee H.-N., Gwangju Institute of Science and Technology, School of Electrical Engineering and Computer Science, Gwangju, 61005, South Korea