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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 6 | Month- June 2024
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Published Paper Details:
Paper Title
Categorization of Cancerous Cervical Cells Using Convolutional Neural Networks and Deep Learning Techniques
Authors
Jeevitha BC, Sahana SR, Thejashree S, Roshan R Nadaf, Mr. Hemanth Kumar
Keywords
Fine-grained classification, cell morphology, deep learning, Pap smear, Herlev dataset.
Abstract
A precise categorization of abnormal cervical cells is critical but difficult. Traditional methods rely on manual or engineered features, while convolutional neural networks (CNN) use deep learning. Prior CNN models didn't consider cell morphology, so this study proposes a CNN method that combines appearance and morphology. The cervical cell dataset was trained with adaptively re-sampled image patches. Several pre-trained CNNs were fine-tuned and evaluated on the Herlev cervical dataset with a five-fold cross-validation. The proposed method achieved higher accuracy by adding morphological information to appearance-based CNN learning, with the best model achieving accuracies of 80%, 70%, 54% and 21% for two-class, four-class, and seven-class classification tasks. Combining morphology with appearance improves classification performance, but the task remains challenging.
IJCRT's Publication Details
Unique Identification Number - IJCRT2305157
Paper ID - 235761
Page Number(s) - b204-b213
Pubished in - Volume 11 | Issue 5 | May 2023
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Jeevitha BC, Sahana SR, Thejashree S, Roshan R Nadaf, Mr. Hemanth Kumar, "Categorization of Cancerous Cervical Cells Using Convolutional Neural Networks and Deep Learning Techniques", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 5, pp.b204-b213, May 2023, Available at :http://www.ijcrt.org/papers/IJCRT2305157.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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