DPE-BoTNeT: Dual Position Encoding Bottleneck Transformer Network for Skin Lesion Classification-Reference-Cited by-同舟云学术

DPE-BoTNeT: Dual Position Encoding Bottleneck Transformer Network for Skin Lesion Classification

Published:2022-03-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
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Author:

Nakai Katsuhiro¹,Han Xian-Hua¹

Affiliation:

1. Yamaguchi University,Graduate School of Science and Technology for Innovation,Japan,753-8511

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9761376/9761399/09761578.pdf?arnumber=9761578

Reference21 articles.

1. Self-Attention with Relative Position Representations

2. Convolutional sequence to sequence learning;gehring,2017

3. Skin le-sion analysis towardmelanoma detection: A challenge at the 2017 internationalsymposium on biomedical imaging (isbi) hosted by theinternational skin imaging collaboration (isic);codella;CoRR,2017

4. The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions;tschandl;Scientific Data,2018

5. Soft Attention Improves Skin Cancer Classification Performance

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