1. Adelaide Research & Scholarship

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Results 1-10 of 29 (Search time: 0.002 seconds).
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PreviewIssue DateTitleAuthor(s)
2020Evolutionary Image Transition and Painting Using Random WalksNeumann, A.; Alexander, B.; Neumann, F.
2013The minimal preprocessing pipelines for the Human Connectome ProjectGlasser, M.F.; Sotiropoulos, S.N.; Wilson, J.A.; Coalson, T.S.; Fischl, B.; Andersson, J.L.; Xu, J.; Jbabdi, S.; Webster, M.; Polimeni, J.R.; Van Essen, D.C.; Jenkinson, M.
2019Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CTXie, Y.; Xia, Y.; Zhang, J.; Song, Y.; Feng, D.; Fulham, M.; Cai, W.
2019An effective density-based clustering and dynamic maintenance framework for evolving medical data streamsAl-Shammari, A.; Zhou, R.; Naseriparsaa, M.; Liu, C.
2015An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cellsLu, Z.; Carneiro, G.; Bradley, A.
2015Multi-target tracking with time-varying clutter rate and detection profile: application to time-lapse cell microscopy sequencesRezatofighi, S.H.; Gould, S.; Vo, B.T.; Vo, B.-N.; Mele, K.; Hartley, R.
2021Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and ActivationsZhuang, B.; Tan, M.; Liu, J.; Liu, L.; Reid, I.; Shen, C.
2021Auto-Rectify Network for Unsupervised Indoor Depth EstimationBian, J.W.; Zhan, H.; Wang, N.; Chin, T.J.; Shen, C.; Reid, I.
2021Learn to Predict Sets Using Feed-Forward Neural NetworksRezatofighi, H.; Kaskman, R.; Taghizadeh Motlagh, S.F.; Shi, Q.; Milan, A.; Cremers, D.; Leal-Taixé, L.; Reid, I.D.
2015Multiplicative approximations, optimal hypervolume distributions, and the choice of the reference pointFriedrich, T.; Neumann, F.; Thyssen, C.

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