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Research
  1. Queen Mary University of London
  2. Research
  3. Publications

Publications: Dr Pengfei Fan

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Shen Z, Mao M, Fan P ( 2024 ) . A Primary Comparison of Diffusion Models and Generative Adversarial Networks for Image Synthesis . Conference: Proceedings of the 2024 7th International Conference on Machine Learning and Machine Intelligence (MLMI)225 - 234 .
Mao M, Shen Z, Fan P ( 2024 ) . Improved Diffusion Model for Fast Image Generation . Conference: Proceedings of the 2024 7th International Conference on Machine Learning and Machine Intelligence (MLMI)209 - 216 .
Fan P, Jiang R, Wang S, Wang X, Zhang Y, Jia D ( 2024 ) . An efficient acoustic energy harvester by using deep learning-based traffic prediction . Energy vol. 308 ,
Fan P, Purwanto E, Li N, Wang J, Tay TT, Wang L, Wang Q ( 2024 ) . Unlocking the Potential of Competition-Based Learning: A Case Study of Kaggle in Big Data Analytics Education . Conference: 2024 10th International Conference on Smart Computing and Communication (ICSCC) vol. 00 , 589 - 595 .
Huang Y, Qian J, Fan P, Liu Y ( 2024 ) . Parameter estimation algorithm based on the combination of cross-correlation and principal component analysis for structured illumination microscopy . Proceedings of SPIE--the International Society for Optical Engineering . Conference: Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Technologies in Optical Systems vol. 13153 ,
Xia W, Qian J, Fan P, Zuo C ( 2024 ) . Tiled and layer-adaptive three-dimensional structured illumination microscopy based on principal component analysis . Proceedings of SPIE--the International Society for Optical Engineering . Conference: Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Imaging Systems vol. 13155 ,
Fan P, Wang Y, Ruddlesden M, Zuo C, Su L ( 2024 ) . Enhanced Light Control in Transmission and Reflection through a Dynamically Deformed Multimode Fiber with Deep Learning . 2024 Conference on Lasers and Electro-Optics, CLEO 2024 .
Fan P, Ruddlesden M, Wang Y, Zhao L, Lu C, Su L ( 2022 ) . Semi-supervised Learning Enabled Scalable High-Spatial-Density Channel Multiplexing over Multimode Fibers . Conference: 2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC) vol. 00 , 1 - 4 .
Fan P, Wang Y, Ruddlesden M, Wang X, Thaha MA, Sun J, Zuo C, Su L ( 2022 ) . Deep Learning Enabled Scalable Calibration of a Dynamically Deformed Multimode Fiber . Advanced Photonics Research2100304 - 2100304 .
Zuo C, Qian J, Feng S, Yin W, Li Y, Fan P, Han J, Qian K et al. ( 2022 ) . Correction: Deep learning in optical metrology: a review . Light: Science & Applications vol. 11 , ( 1 )
Zuo C, Qian J, Feng S, Yin W, Li Y, Fan P, Han J, Qian K et al. ( 2022 ) . Deep learning in optical metrology: a review . Light: Science & Applications vol. 11 , ( 1 )
Fan P, Ruddlesden M, Wang Y, Zhao L, Lu C, Su L ( 2021 ) . Learning Enabled Continuous Transmission of Spatially Distributed Information through Multimode Fibers . Laser and Photonics Reviews
Fan P, Ruddlesden M, Wang Y, Su L . Speckle Reconstruction with Corruption through Multimode Fibers Using Deep Learning . Conference: Conference on Lasers and Electro-Optics
Fan P, Deng L, Su L ( 2018 ) . Light Propagation Prediction through Multimode Optical Fibers with a Deep Neural Network . Conference: 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) vol. 00 , 1080 - 1084 .
Pengfei F, Tianrui Z, SU L ( 2018 ) . Deep learning the high variability and randomness inside multimode fibres . arXiv:1807.09351 [physics.optics]
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