Learning to Recognize Chest-Xray Images Faster and More Efficiently Based on Multi-Kernel Depthwise Convolution-Reference-Cited by-同舟云学术

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Learning to Recognize Chest-Xray Images Faster and More Efficiently Based on Multi-Kernel Depthwise Convolution

Published:2020 Issue: Volume:8 Page:37265-37274
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hu Mengjie^ORCID,Lin Hezheng,Fan Zimeng,Gao Wenjie,Yang Lu,Liu Chun^ORCID,Song Qing^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09000602.pdf?arnumber=9000602

Cited by 32 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. Automated and reliable detection of multi-diseases on chest X-ray images using optimized ensemble transfer learning;Expert Systems with Applications;2024-07

2. Learning group-wise spatial attention and label dependencies for multi-task thoracic disease classification;Neurocomputing;2024-03

3. Multiple thoracic diseases detection from X-rays using CX-Ultranet;Health and Technology;2024-02-08

4. YOLO‐UNet Architecture for Detecting and Segmenting the Localized MRI Brain Tumor Image;Applied Computational Intelligence and Soft Computing;2024-01

5. Multi-Label Classification of Lung Diseases Using Deep Learning;IEEE Access;2024

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