SegQNAS: Quantum-inspired Neural Architecture Search applied to Medical Image Semantic Segmentation
Author:
Affiliation:
1. PUC-Rio,Dept. of Electrical Engineering,Rio de Janeiro,Brazil
2. UERJ,Dept. of Informatics and Computer Science,Rio de Janeiro,Brazil
3. University of Sharjah,Dept. of Electrical Engineering,Sharjah,United Arab Emirates
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191869.pdf?arnumber=10191869
Reference25 articles.
1. Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
2. Neural architecture search: A survey;elsken;The Journal of Machine Learning Research,2019
3. Image Segmentation Using Deep Learning: A Survey
4. Neural architecture search with bayesian optimisation and optimal transport;kandasamy;Advances in neural information processing systems,2018
5. Heed the noise in performance evaluations in neural architecture search
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