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Yongliang Qiao
Yongliang Qiao
Australian Institute for Machine Learning (AIML) ,The University of Adelaide
Verified email at adelaide.edu.au
Title
Cited by
Cited by
Year
Cattle segmentation and contour extraction based on Mask R-CNN for precision livestock farming
Y Qiao, M Truman, S Sukkarieh
Computers and Electronics in Agriculture 165, 104958, 2019
1672019
CNN feature based graph convolutional network for weed and crop recognition in smart farming
H Jiang, C Zhang, Y Qiao, Z Zhang, W Zhang, C Song
Computers and electronics in agriculture 174, 105450, 2020
1522020
Intelligent perception for cattle monitoring: A review for cattle identification, body condition score evaluation, and weight estimation
Y Qiao, H Kong, C Clark, S Lomax, D Su, S Eiffert, S Sukkarieh
Computers and Electronics in Agriculture 185, 106143, 2021
992021
Individual cattle identification using a deep learning based framework
Y Qiao, D Su, H Kong, S Sukkarieh, S Lomax, C Clark
IFAC-PapersOnLine 52 (30), 318-323, 2019
682019
Data augmentation for deep learning based semantic segmentation and crop-weed classification in agricultural robotics
D Su, H Kong, Y Qiao, S Sukkarieh
Computers and Electronics in Agriculture 190, 106418, 2021
642021
An improved YOLOv5-based vegetable disease detection method
J Li, Y Qiao, S Liu, J Zhang, Z Yang, M Wang
Computers and Electronics in Agriculture 202, 107345, 2022
402022
C3D-ConvLSTM based cow behaviour classification using video data for precision livestock farming
Y Qiao, Y Guo, K Yu, D He
Computers and Electronics in Agriculture 193, 106650, 2022
382022
Real time detection of inter-row ryegrass in wheat farms using deep learning
D Su, Y Qiao, H Kong, S Sukkarieh
Biosystems Engineering 204, 198-211, 2021
382021
Weed recognition based on SVM-DS multi-feature fusion.
D He, Y Qiao, P Li, Z Gao, HY Li, JL Tang
Nongye Jixie Xuebao= Transactions of the Chinese Society for Agricultural …, 2013
342013
BiLSTM-based individual cattle identification for automated precision livestock farming
Y Qiao, D Su, H Kong, S Sukkarieh, S Lomax, C Clark
2020 IEEE 16th International Conference on Automation Science and …, 2020
332020
The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming
S Wang, H Jiang, Y Qiao, S Jiang, H Lin, Q Sun
Sensors 22 (17), 6541, 2022
322022
Intelligent perception-based cattle lameness detection and behaviour recognition: A review
Y Qiao, H Kong, C Clark, S Lomax, D Su, S Eiffert, S Sukkarieh
Animals 11 (11), 3033, 2021
312021
Identification method of multi-feature weed based on multi-spectral images and data mining
C Zhao, D He, Y Qiao
Transactions of the Chinese Society of Agricultural Engineering 29 (2), 192-198, 2013
302013
Cattle body detection based on YOLOv5-ASFF for precision livestock farming
Y Qiao, Y Guo, D He
Computers and Electronics in Agriculture 204, 107579, 2023
282023
Multiframe-based high dynamic range monocular vision system for advanced driver assistance systems
Y Li, Y Qiao, Y Ruichek
IEEE Sensors Journal 15 (10), 5433-5441, 2015
262015
ConvNet and LSH-based visual localization using localized sequence matching
Y Qiao, C Cappelle, Y Ruichek, T Yang
Sensors 19 (11), 2439, 2019
212019
Data augmentation for deep learning based cattle segmentation in precision livestock farming
Y Qiao, D Su, H Kong, S Sukkarieh, S Lomax, C Clark
2020 IEEE 16th International Conference on Automation Science and …, 2020
202020
Visual localization across seasons using sequence matching based on multi-feature combination
Y Qiao, C Cappelle, Y Ruichek
Sensors 17 (11), 2442, 2017
182017
Filtering for systems subject to unknown inputs without a priori initial information
H Kong, M Shan, D Su, Y Qiao, A Al-Azzawi, S Sukkarieh
Automatica 120, 109122, 2020
172020
Automated aerial animal detection when spatial resolution conditions are varied
J Brown, Y Qiao, C Clark, S Lomax, K Rafique, S Sukkarieh
Computers and Electronics in Agriculture 193, 106689, 2022
162022
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