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Results 1-9 of 9 (Search time: 0.002 seconds).
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PreviewIssue DateTitleAuthor(s)
2018Active learning from noisy tagged imagesAbbasnejad, M.E.; Dick, A.R.; Shi, Q.; Hengel, A.V.D.; British Machine Vision Conference 2018 (BMVC 2018) (3 Sep 2018 - 6 Sep 2018 : Newcastle upon Tyne)
2019Adaptive neuro-surrogate-based optimisation method for wave energy converters placement optimisationNeshat, M.; Abbasnejad, E.; Shi, Q.; Alexander, B.; Wagner, M.; Gedeon, T.; Wong, K.W.; Lee, M.; 26th International Conference on Neural Information Processing (ICONIP) (12 Dec 2019 - 15 Dec 2019 : Sydney, Australia)
2017MPGL: An efficient matching pursuit method for generalized LASSOGong, D.; Tan, M.; Zhang, Y.; Van Den Hengel, A.; Shi, Q.; 31st AAAI Conference on Artificial Intelligence (AAAI-17) (4 Feb 2017 - 9 Feb 2017 : San Francisco)
2018Joint learning of set cardinality and state distributionRezatofighi, H.; Milan, A.; Shi, Q.; Dick, A.; Reid, I.; AAAI Conference on Artificial Intelligence (AAAI) (2 Feb 2018 - 7 Feb 2018 : New Orleans, USA)
2017Solving constrained combinatorial optimization problems via MAP inference without high-order penaltiesZhang, Z.; Shi, Q.; McAuley, J.; Wei, W.; Zhang, Y.; Yao, R.; Van Den Hengel, A.; Thirty-first AAAI Conference on Artificial Intelligence (AAAI-17) (4 Feb 2017 - 9 Feb 2017 : San Francisco)
2017Part-based robust tracking using online latent structured learningYao, R.; Shi, Q.; Shen, C.; Zhang, Y.; Van Den Hengel, A.
2020Accurate tensor completion via adaptive low-rank representationZhang, L.; Wei, W.; Shi, Q.; Shen, C.; van den Hengel, A.; Zhang, Y.
2019MPTV: matching pursuit based total variation minimization for image deconvolutionGong, D.; Tan, M.; Shi, Q.; van den Hengel, A.; Zhang, Y.
2021Wind turbine power output prediction using a new hybrid neuro-evolutionary methodNeshat, M.; Nezhad, M.M.; Abbasnejad, E.; Mirjalili, S.; Groppi, D.; Heydari, A.; Tjernberg, L.B.; Astiaso Garcia, D.; Alexander, B.; Shi, Q.; Wagner, M.

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