Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification-Reference-Cited by-同舟云学术

Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification

Published:2018 Issue: Volume: Page:115-123
ISSN:0302-9743
Container-title:Understanding and Interpreting Machine Learning in Medical Image Computing Applications
language:
Short-container-title:

Author:

Van Molle Pieter,De Strooper Miguel,Verbelen Tim,Vankeirsbilck Bert,Simoens Pieter,Dhoedt Bart

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-02628-8_13

Reference18 articles.

1. Lecture Notes in Computer Science;DC Cireşan,2013

2. Codella, N.C., et al.: Deep learning ensembles for melanoma recognition in dermoscopy images. IBM J. Res. Dev. 61(4), 1–5 (2017)

3. Esteva, A., et al.: Dermatologist-level classification of skin cancer with deep neural networks. Nature 542(7639), 115 (2017)

4. Fakoor, R., Ladhak, F., Nazi, A., Huber, M.: Using deep learning to enhance cancer diagnosis and classification. In: International Conference on Machine Learning, vol. 28 (2013)

5. Haenssle, H.A., et al.: Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Ann. Oncol. 29, 1836–1842 (2018)

Cited by 40 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Skin cancer identification utilizing deep learning: A survey;IET Image Processing;2024-09-02

2. Computer-Aided Classification of Melanoma: A Comprehensive Survey;Archives of Computational Methods in Engineering;2024-06-06

3. A Novel Black-Box Complementary Explanation Approach for Thorax Multi-Label Classification;2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET);2024-05-16

4. A novel joint segmentation approach for wafer surface defect classification based on blended network structure;Journal of Intelligent Manufacturing;2024-03-13

5. Evaluation of Explainable AI Methods in CNN Classifiers of COVID-19 CT Images;IFMBE Proceedings;2024