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ORCIDKyaw Kyaw Htike
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2010 – 2019
- 2018
[j7]Kyaw Kyaw Htike:
Predicting rainfall using neural nets. Int. J. Comput. Sci. Eng. 17(4): 353-364 (2018)- [j6]Kyaw Kyaw Htike:
Efficient holistic feature basis learning for pedestrian detection. Int. J. Comput. Vis. Robotics 8(1): 74-84 (2018) - [j5]Kyaw Kyaw Htike:
Forests of unstable hierarchical clusters for pattern classification. Soft Comput. 22(5): 1711-1718 (2018) - 2017
- [j4]Kyaw Kyaw Htike:
A review on data-driven learning of a talking head model. Int. J. Intell. Syst. Technol. Appl. 16(2): 169-190 (2017) - [j3]Kyaw Kyaw Htike:
Hidden-layer Ensemble Fusion of MLP Neural Networks for Pedestrian Detection. Informatica (Slovenia) 41(1) (2017) - [j2]Kyaw Kyaw Htike:
Efficient determination of the number of weak learners in AdaBoost. J. Exp. Theor. Artif. Intell. 29(5): 967-982 (2017) - 2016
- [j1]Kyaw Kyaw Htike, David C. Hogg
:
Adapting pedestrian detectors to new domains: A comprehensive review. Eng. Appl. Artif. Intell. 50: 142-158 (2016) - 2014
- [b1]Kyaw Kyaw Htike:
Domain adaptation for pedestrian detection. University of Leeds, UK, 2014 - [c3]Kyaw Kyaw Htike, David C. Hogg:
Unsupervised Detector Adaptation by Joint Dataset Feature Learning. ICCVG 2014: 270-277 - [c2]Kyaw Kyaw Htike, David C. Hogg:
Weakly supervised pedestrian detector training by unsupervised prior learning and cue fusion in videos. ICIP 2014: 2338-2342 - [c1]Kyaw Kyaw Htike, David C. Hogg:
Efficient Non-iterative Domain Adaptation of Pedestrian Detectors to Video Scenes. ICPR 2014: 654-659
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