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High expertise and experienced gynecologist are required for an accurate diagnosis of cervical cancer. To reduce their burden, a model is proposed, based on deep learning that automatically classifies the cervix types. This paper presents Modified Deep Convolutional Neural Networks namely Modified VGG16 (MVGG16), Modified VGG19 (MVGG19), Modified ResNet50 (MRN50), Modified InceptionV3 (MIV3), and Modified InceptionResNetV2 (MIRNV2) for the classification of cervix type images. These modified networks are implemented using a Multiclass Support Vector Machine classifier. The performance metrics are tabulated and compared with pre-trained models. The simulation results show that MIRNV2 achieves the best performance compared to other models with an overall Accuracy of 92.91% and a Kappa score of 0.88. MIRNV2 model also gives better classification accuracy of 96.62% for type 1, 93.58% for type 2, and 95.61% for type 3 cervix images. Hence, this facilitates the application of MIRNV2 as a diagnostic tool to assist the gynecologist in the classification of cervix type images.<\/jats:p>","DOI":"10.1177\/09544119221143441","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T07:35:27Z","timestamp":1671780927000},"page":"265-281","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Transfer learning supported accurate assessment of multiclass cervix type images"],"prefix":"10.1177","volume":"237","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7911-6564","authenticated-orcid":false,"given":"Thendral","family":"Natarajan","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering, Meenakshi College of Engineering, Anna University, Chennai, Tamil Nadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lakshmi","family":"Devan","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, St. Joseph\u2019s College of Engineering, Anna University, Chennai, Tamil Nadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"bibr1-09544119221143441","doi-asserted-by":"publisher","DOI":"10.4103\/2278-330X.187574"},{"key":"bibr2-09544119221143441","volume-title":"WHO Guidelines for screening and treatment of precancerous lesions for cervical cancer prevention","author":"World Health Organization","year":"2013"},{"key":"bibr3-09544119221143441","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-68252-3"},{"key":"bibr4-09544119221143441","doi-asserted-by":"publisher","DOI":"10.1016\/j.ogc.2013.02.002"},{"key":"bibr5-09544119221143441","doi-asserted-by":"publisher","DOI":"10.1002\/9781444312744"},{"key":"bibr6-09544119221143441","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdp471"},{"key":"bibr7-09544119221143441","volume-title":"Medical image understanding and analysis. 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