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Diabetic Foot Ulcers Grand Challenge : Second Challenge, DFUC 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings / edited by Moi Hoon Yap, Bill Cassidy, Connah Kendrick.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 13183
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 13183
- Language:
- English
- Subjects (All):
- Image processing-Digital techniques.
- Computer vision.
- Machine learning.
- Computer science-Mathematics.
- Mathematical statistics.
- Social sciences-Data processing.
- Computers.
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Machine Learning.
- Probability and Statistics in Computer Science.
- Computer Application in Social and Behavioral Sciences.
- Computing Milieux.
- Local Subjects:
- Computer Imaging, Vision, Pattern Recognition and Graphics.
- Machine Learning.
- Probability and Statistics in Computer Science.
- Computer Application in Social and Behavioral Sciences.
- Computing Milieux.
- Physical Description:
- 1 online resource (IX, 121 pages) : 52 illustrations, 47 illustrations in color.
- Edition:
- 1st ed. 2022.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- System Details:
- text file PDF
- Summary:
- This book constitutes the Second Diabetic Foot Ulcers Grand Challenge, DFUC 2021, which was held on September 27, 2021, in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. The challenge took place virtually due to the COVID-19 pandemic. The 6 full papers included in this book were carefully reviewed and selected from 14 submissions. There is also an overview paper on the challenge and datasets and one summary paper of DFUC 2021. .
- Contents:
- Development of Diabetic Foot Ulcer Datasets: An Overview
- DFUC2021 Challenge Papers
- Convolutional Nets Versus Vision Transformers for Diabetic Foot Ulcer Classification
- Boosting EffcientNets Ensemble Performance via Pseudo-Labels and Synthetic Images by pix2pixHD for Infection and Ischaemia Classification in Diabetic Foot Ulcers
- Bias Adjustable Activation Network for Imbalanced data - Diabetic Foot Ulcer Challenge 2021
- Effcient Multi-model Vision Transformer based on Feature Fusion for Classification of DFUC2021 Challenge
- Diabetic Foot Ulcer Classification using Well-known Deep Learning Architectures
- Diabetic Foot Ulcer Grand Challenge 2021: Evaluation and Summary
- Post Challenge Paper
- Deep Subspace analysing for Semi-Supervised multi-label classification of Diabetic Foot Ulcer.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-94907-5
- 9783030949075
- Access Restriction:
- Restricted for use by site license.
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