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Disambiguation of "Zhou, Weimin"

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Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks.

, and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160D. SPIE, (2020)

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Zhou Zhou

Zhou Zhou

Weimin Xi

Weimin Liu

Weimin Gan

 

Other publications of authors with the same name

Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements., , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160Q. SPIE, (2020)Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks., and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160D. SPIE, (2020)Learning stochastic object model from noisy imaging measurements using AmbientGANs., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10952 of SPIE Proceedings, page 109520M. SPIE, (2019)Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks., and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10952 of SPIE Proceedings, page 1095209. SPIE, (2019)Increase in Axial Compressibility in a Spinning Van der Waals Gas., , , and . Entropy, 23 (2): 137 (2021)A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods., , , and . IEEE Trans. Medical Imaging, 41 (5): 1114-1124 (2022)Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)Supervised learning-based ideal observer approximation for joint detection and estimation tasks., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11599 of SPIE Proceedings, SPIE, (2021)A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise., and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12035 of SPIE Proceedings, SPIE, (2022)Learning efficient channels with a dual loss autoencoder., , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160C. SPIE, (2020)