Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images-Reference-Cited by-同舟云学术

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Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images

Published:2021-03 Issue:3 Volume:32 Page:932-946
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Paluru Naveen^ORCID,Dayal Aveen^ORCID,Jenssen Havard Bjorke,Sakinis Tomas^ORCID,Cenkeramaddi Linga Reddy,Prakash Jaya,Yalavarthy Phaneendra K.^ORCID

Funder

WIPRO GECDS Collaborative Laboratory of Artificial Intelligence in Healthcare and Medical Imaging

Indo-Norwegian Collaboration in Autonomous Cyber-Physical Systems

INTPART

Norwegian Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/9365681/09349153.pdf?arnumber=9349153

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