An efficient deep learning approach to detect skin cancer using image data

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Chowdhury, Yaser Al Rahman, Ahmed, S.K.Saqlayen, Faisal, Abdullah All, Zahir, Zerjiss
مؤلفون آخرون:	Alam, Dr. Md. Ashraful
التنسيق:	أطروحة
اللغة:	English
منشور في:	Brac University 2023
الموضوعات:	Classification Detection deep learning Accuracy Neural network Acquisition Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing > Digital techniques.
الوصول للمادة أونلاين:	http://hdl.handle.net/10361/19295

id	10361-19295
record_format	dspace
spelling	10361-192952023-08-06T21:02:02Z An efficient deep learning approach to detect skin cancer using image data Chowdhury, Yaser Al Rahman Ahmed, S.K.Saqlayen Faisal, Abdullah All Zahir, Zerjiss Alam, Dr. Md. Ashraful Department of Computer Science and Engineering, Brac University Classification Detection deep learning Accuracy Neural network Acquisition Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing -- Digital techniques. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 40-41). We propose and demonstrate an efficient deep learning approach to classify skin can cer using image data. The proposed approach is composed of several stages which are data acquisition, preprocessing and classification. For classifying skin cancer using image data and deep learning, four different convolutional neural network ar chitectures, EfficientNetV2B3, EfficientNetV2s, InceptionNetV3 and DenseNet121 were used on this work. The CNN models achieved accuracies of 83%, 86%, 84% and 88% respectively on a testing split of the HAM10000 dataset. Moreover, each of the CNN models were ensembled in two different ways, one is where all the predictions from the four models were averaged and the other one is based on K-Nearest Neigh bors approach where features from each of the CNN models were combined to fit a KNN model. The ensemble through averaging predictions achieved an accuracy of 90% and the ensemble based on K-Nearest Neighbors achieved an accuracy of 92%. Moreover, we demonstrated each of the CNN models using Explainable AI. Yaser Al Rahman Chowdhury S.K.Saqlayen Ahmed Abdullah All Faisal Zerjiss Zahir B. Computer Science and Engineering 2023-08-06T05:57:52Z 2023-08-06T05:57:52Z 2023 2023-01 Thesis ID: 17201050 ID: 18101555 ID: 18101522 ID: 18101498 http://hdl.handle.net/10361/19295 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 41 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Classification Detection deep learning Accuracy Neural network Acquisition Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing -- Digital techniques.
spellingShingle	Classification Detection deep learning Accuracy Neural network Acquisition Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Image processing -- Digital techniques. Chowdhury, Yaser Al Rahman Ahmed, S.K.Saqlayen Faisal, Abdullah All Zahir, Zerjiss An efficient deep learning approach to detect skin cancer using image data
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
author2	Alam, Dr. Md. Ashraful
author_facet	Alam, Dr. Md. Ashraful Chowdhury, Yaser Al Rahman Ahmed, S.K.Saqlayen Faisal, Abdullah All Zahir, Zerjiss
format	Thesis
author	Chowdhury, Yaser Al Rahman Ahmed, S.K.Saqlayen Faisal, Abdullah All Zahir, Zerjiss
author_sort	Chowdhury, Yaser Al Rahman
title	An efficient deep learning approach to detect skin cancer using image data
title_short	An efficient deep learning approach to detect skin cancer using image data
title_full	An efficient deep learning approach to detect skin cancer using image data
title_fullStr	An efficient deep learning approach to detect skin cancer using image data
title_full_unstemmed	An efficient deep learning approach to detect skin cancer using image data
title_sort	efficient deep learning approach to detect skin cancer using image data
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/19295
work_keys_str_mv	AT chowdhuryyaseralrahman anefficientdeeplearningapproachtodetectskincancerusingimagedata AT ahmedsksaqlayen anefficientdeeplearningapproachtodetectskincancerusingimagedata AT faisalabdullahall anefficientdeeplearningapproachtodetectskincancerusingimagedata AT zahirzerjiss anefficientdeeplearningapproachtodetectskincancerusingimagedata AT chowdhuryyaseralrahman efficientdeeplearningapproachtodetectskincancerusingimagedata AT ahmedsksaqlayen efficientdeeplearningapproachtodetectskincancerusingimagedata AT faisalabdullahall efficientdeeplearningapproachtodetectskincancerusingimagedata AT zahirzerjiss efficientdeeplearningapproachtodetectskincancerusingimagedata
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An efficient deep learning approach to detect skin cancer using image data

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