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ORCIDKun Zhao 0001
Person information
- affiliation: University of Queensland, School of ITEE, Brisbane, Australia
Other persons with the same name
- Kun Zhao — disambiguation page
- Kun Zhao 0002
![[0000-0003-2326-4343]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-2326-4343")
— Xi'an Jiaotong University, School of Electronic and Information Engineering, Xi'an, China - Kun Zhao 0003 — Suncorp Group, Brisbane, Australia (and 2 more)
- Kun Zhao 0004 — IBM Research Tokyo, Japan (and 1 more)
- Kun Zhao 0005 — Sony Research Center, Lund, Sweden (and 2 more)
- Kun Zhao 0006 — Xi'an Jiaotong University, School of Electrical Engineering, Xi'an, China (and 1 more)
- Kun Zhao 0007 — University of Pittsburgh, Department of Electrical and Computer Engineering, PA, USA (and 1 more)
- Kun Zhao 0008 — Nanjing University, School of Atmospheric Sciences, Key Laboratory of Mesoscale Severe Weather, Joint Center for Atmospheric Radar Research of CMA/NJU, Nanjing, China
- Kun Zhao 0009 — Foxconn Industrial Internet Company Ltd., Shenzhen, China
- Kun Zhao 0010 — East China Normal University, Engineering Center of SHMEC for Space Information and GNSS, Shanghai, China (and 1 more)
- Kun Zhao 0011 — China University of Petroleum, State Key Laboratory of Petroleum Resources and Prospecting, College of New Energy and Materials, Beijing, China
- Kun Zhao 0012 — Harbin Engineering University, College of Automation, Harbin, China
- Kun Zhao 0013 — Tulane University, Department of Mathematics, New Orleans, LA, USA
- Kun Zhao 0014 — Chinese Academy of Sciences, Institute of Automation, Brainnetome Center & National Laboratory of Pattern Recognition, Beijing, China (and 1 more)
- Kun Zhao 0015 — Beijing University of Posts and Telecommunications, School of Information and Communication Engineering, Beijing Key Laboratory of Network System Architecture and Convergence, Beijing, China
- Kun Zhao 0016 — China Aerodynamics Research and Development Centre, Key Laboratory of Aerodynamic Noise Control, Mianyang, China
- Kun Zhao 0017 — University of Melbourne, Melbourne School of Psychological Sciences, Melbourne, Australia
- Kun Zhao 0018 — School of Computer Science, Wuhan University, Wuhan, China
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2020 – today
- 2023
[j6]Can Peng, Kun Zhao, Sam Maksoud, Tianren Wang, Brian C. Lovell:
DIODE: Dilatable Incremental Object Detection. Pattern Recognit. 136: 109244 (2023)- 2022
- [c17]Can Peng, Kun Zhao, Tianren Wang, Meng Li, Brian C. Lovell:
Few-Shot Class-Incremental Learning from an Open-Set Perspective. ECCV (25) 2022: 382-397 - [c16]Sarah Alhammad, Teng Zhang, Kun Zhao, Peter Hobson, Anthony Jennings, Brian C. Lovell:
Efficient Cell Labelling for Gram Stain WSIs. ICPR 2022: 4226-4233 - [i15]Can Peng, Kun Zhao, Tianren Wang, Meng Li, Brian C. Lovell:
Few-Shot Class-Incremental Learning from an Open-Set Perspective. CoRR abs/2208.00147 (2022) - 2021
- [j5]Can Peng, Kun Zhao, Sam Maksoud, Meng Li, Brian C. Lovell:
SID: Incremental learning for anchor-free object detection via Selective and Inter-related Distillation. Comput. Vis. Image Underst. 210: 103229 (2021) - [c15]Sarah Alhammad, Kun Zhao, Anthony Jennings, Peter Hobson, Daniel F. Smith, Brett Baker, Justin Staweno, Brian C. Lovell:
Efficient DNN-Based Classification of Whole Slide Gram Stain Images for Microbiology. DICTA 2021: 1-8 - [c14]Meng Li, Kun Zhao, Can Peng, Peter Hobson, Tony Jennings, Brian C. Lovell:
Deep Adaptive Few Example Learning for Microscopy Image Cell Counting. DICTA 2021: 1-7 - [i14]Sam Maksoud, Kun Zhao, Can Peng, Brian C. Lovell:
Scalable Bayesian Deep Learning with Kernel Seed Networks. CoRR abs/2104.09005 (2021) - [i13]Can Peng, Kun Zhao, Sam Maksoud, Tianren Wang, Brian C. Lovell:
DIODE: Dilatable Incremental Object Detection. CoRR abs/2108.05627 (2021) - 2020
- [j4]Teng Zhang, Liangchen Liu, Kun Zhao, Arnold Wiliem, Graham Hemson, Brian C. Lovell:
Omni-supervised joint detection and pose estimation for wild animals. Pattern Recognit. Lett. 132: 84-90 (2020) - [j3]Can Peng, Kun Zhao, Brian C. Lovell:
Faster ILOD: Incremental learning for object detectors based on faster RCNN. Pattern Recognit. Lett. 140: 109-115 (2020) - [c13]Sam Maksoud, Kun Zhao, Peter Hobson, Anthony Jennings, Brian C. Lovell:
SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image Classification. CVPR 2020: 3861-3870 - [i12]Can Peng, Kun Zhao, Brian C. Lovell:
Faster ILOD: Incremental Learning for Object Detectors based on Faster RCNN. CoRR abs/2003.03901 (2020) - [i11]Sam Maksoud, Kun Zhao, Peter Hobson, Anthony Jennings, Brian C. Lovell:
SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image Classification. CoRR abs/2003.05080 (2020) - [i10]Can Peng, Kun Zhao, Sam Maksoud, Meng Li, Brian C. Lovell:
SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation. CoRR abs/2012.15439 (2020)
2010 – 2019
- 2019
- [j2]Kun Zhao, Arnold Wiliem, Shaokang Chen, Brian C. Lovell:
Convex class model on symmetric positive definite manifolds. Image Vis. Comput. 87: 57-67 (2019) - [c12]Can Peng, Kun Zhao, Arnold Wiliem, Teng Zhang, Peter Hobson, Anthony Jennings, Brian C. Lovell:
To What Extent Does Downsampling, Compression, and Data Scarcity Impact Renal Image Analysis? DICTA 2019: 1-8 - [c11]Liangchen Liu, Teng Zhang, Kun Zhao, Arnold Wiliem, Kieren Astin-Walmsley, Brian C. Lovell:
Deep Inspection: An Electrical Distribution Pole Parts Study VIA Deep Neural Networks. ICIP 2019: 4170-4174 - [c10]Sam Maksoud, Arnold Wiliem, Kun Zhao, Teng Zhang, Lin Wu, Brian C. Lovell:
CORAL8: Concurrent Object Regression for Area Localization in Medical Image Panels. MICCAI (1) 2019: 432-441 - [c9]Meng Li, Lin Wu, Arnold Wiliem, Kun Zhao, Teng Zhang, Brian C. Lovell:
Deep Instance-Level Hard Negative Mining Model for Histopathology Images. MICCAI (1) 2019: 514-522 - [i9]Sam Maksoud, Arnold Wiliem, Kun Zhao, Teng Zhang, Lin Wu, Brian C. Lovell:
CORAL8: Concurrent Object Regression for Area Localization in Medical Image Panels. CoRR abs/1906.09676 (2019) - [i8]Meng Li, Lin Wu, Arnold Wiliem, Kun Zhao, Teng Zhang, Brian C. Lovell:
Deep Instance-Level Hard Negative Mining Model for Histopathology Images. CoRR abs/1906.09681 (2019) - [i7]Liangchen Liu, Teng Zhang, Kun Zhao, Arnold Wiliem, Kieren Astin-Walmsley, Brian C. Lovell:
Deep inspection: an electrical distribution pole parts study via deep neural networks. CoRR abs/1907.06844 (2019) - [i6]Can Peng, Kun Zhao, Arnold Wiliem, Teng Zhang, Peter Hobson, Anthony Jennings, Brian C. Lovell:
To What Extent Does Downsampling, Compression, and Data Scarcity Impact Renal Image Analysis? CoRR abs/1909.09945 (2019) - 2018
- [c8]Kun Zhao, Yu Ji Jerry Tang, Teng Zhang, Johanna Carvajal, Daniel F. Smith, Arnold Wiliem, Peter Hobson, Anthony Jennings, Brian C. Lovell:
DGDI: A Dataset for Detecting Glomeruli on Renal Direct Immunofluorescence. DICTA 2018: 1-7 - [c7]Teng Zhang, Johanna Carvajal, Daniel F. Smith, Kun Zhao, Arnold Wiliem, Peter Hobson, Anthony Jennings, Brian C. Lovell:
SlideNet: Fast and Accurate Slide Quality Assessment Based on Deep Neural Networks. ICPR 2018: 2314-2319 - [i5]Teng Zhang, Johanna Carvajal, Daniel F. Smith, Kun Zhao, Arnold Wiliem, Peter Hobson, Anthony Jennings, Brian C. Lovell:
SlideNet: Fast and Accurate Slide Quality Assessment Based on Deep Neural Networks. CoRR abs/1803.07240 (2018) - [i4]Kun Zhao, Arnold Wiliem, Shaokang Chen, Brian C. Lovell:
Convex Class Model on Symmetric Positive Definite Manifolds. CoRR abs/1806.05343 (2018) - 2017
- [c6]Johanna Carvajal, Daniel F. Smith, Kun Zhao, Arnold Wiliem, Paul Finucane, Peter Hobson, Anthony Jennings, Rodney McDougall, Brian C. Lovell:
An Early Experience Toward Developing Computer Aided Diagnosis for Gram-Stained Smears Images. CVPR Workshops 2017: 814-820 - 2016
- [b1]Kun Zhao:
Fast and accurate image and video analysis on Riemannian manifolds. University of Queensland, Australia, 2016 - [j1]Kun Zhao, Azadeh Alavi, Arnold Wiliem, Brian C. Lovell:
Efficient clustering on Riemannian manifolds: A kernelised random projection approach. Pattern Recognit. 51: 333-345 (2016) - [c5]Kun Zhao, Arnold Wiliem, Shaokang Chen, Brian C. Lovell:
Manifold convex hull (MACH): Satisfying a need for SPD. ICIP 2016: 251-255 - [c4]Kun Zhao, Siqi Yang, Arnold Wiliem, Brian C. Lovell:
Landmark manifold: Revisiting the Riemannian manifold approach for facial emotion recognition. ICPR 2016: 1095-1100 - [c3]Liangchen Liu, Arnold Wiliem, Shaokang Chen, Kun Zhao, Brian C. Lovell:
Determining the best attributes for surveillance video keywords generation. ISBA 2016: 1-7 - [i3]Liangchen Liu, Arnold Wiliem, Shaokang Chen, Kun Zhao, Brian C. Lovell:
Determining the best attributes for surveillance video keywords generation. CoRR abs/1602.06539 (2016) - 2015
- [c2]Kun Zhao, Arnold Wiliem, Brian C. Lovell:
Kernelised orthonormal random projection on grassmann manifolds with applications to action and gait-based gender recognition. ISBA 2015: 1-6 - [i2]Kun Zhao, Azadeh Alavi, Arnold Wiliem, Brian C. Lovell:
Efficient Clustering on Riemannian Manifolds: A Kernelised Random Projection Approach. CoRR abs/1509.05536 (2015) - 2014
- [c1]Azadeh Alavi, Arnold Wiliem, Kun Zhao, Brian C. Lovell, Conrad Sanderson:
Random projections on manifolds of Symmetric Positive Definite matrices for image classification. WACV 2014: 301-308 - [i1]Azadeh Alavi, Arnold Wiliem, Kun Zhao, Brian C. Lovell, Conrad Sanderson:
Random Projections on Manifolds of Symmetric Positive Definite Matrices for Image Classification. CoRR abs/1403.0700 (2014)
Coauthor Index
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