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Jiexiong Tang
Title
Cited by
Cited by
Year
Extreme learning machine for multilayer perceptron
J Tang, C Deng, GB Huang
IEEE Transactions on Neural Networks and Learning Systems, 2015
12962015
Compressed-domain ship detection on spaceborne optical image using deep neural network and extreme learning machine
J Tang, C Deng, GB Huang, B Zhao
IEEE transactions on geoscience and remote sensing 53 (3), 1174-1185, 2014
4212014
Extreme learning machines: new trends and applications
CW Deng, GB Huang, J Xu, JX Tang
Science China information sciences 2 (58), 1-16, 2015
1272015
GCNv2: Efficient Correspondence Prediction for Real-Time SLAM
J Tang, L Ericson, J Folkesson, P Jensfelt
arXiv:1902.11046, 2019
752019
Geometric correspondence network for camera motion estimation
J Tang, J Folkesson, P Jensfelt
IEEE Robotics and Automation Letters 3 (2), 1010-1017, 2018
362018
A fast learning algorithm for multi-layer extreme learning machine
J Tang, C Deng, GB Huang, J Hou
2014 IEEE International Conference on Image Processing (ICIP), 175-178, 2014
242014
Self-supervised 3d keypoint learning for ego-motion estimation
J Tang, R Ambrus, V Guizilini, S Pillai, H Kim, P Jensfelt, A Gaidon
Conference on Robot Learning, 2085-2103, 2021
232021
Neural outlier rejection for self-supervised keypoint learning
J Tang, H Kim, V Guizilini, S Pillai, R Ambrus
arXiv preprint arXiv:1912.10615, 2019
142019
Sparse2Dense: From Direct Sparse Odometry to Dense 3-D Reconstruction
J Tang, J Folkesson, P Jensfelt
IEEE Robotics and Automation Letters 4 (2), 530 - 537, 2019
132019
Systems and methods for detecting and matching keypoints between different views of a scene
J Tang, RA Ambrus, V Guizilini, S Pillai, H Kim
US Patent 11,531,892, 2022
32022
极限学习机: 新趋势与新应用
CW Deng, GB Huang, J Xu, JX Tang
Science China Information Sciences 58, 1-16, 2015
32015
Keypoint matching using graph convolutions
J Tang, RA Ambrus, J Li, V Guizilini, S Pillai, AD Gaidon
US Patent App. 17/231,905, 2021
22021
Self-supervised 3d keypoint learning for monocular visual odometry
J Tang, RA Ambrus, V Guizilini, S Pillai, H Kim, AD Gaidon
US Patent App. 17/093,393, 2021
22021
Learning algorithms for digital reconstruction of Van Gogh’s drawings
Y Zeng, J Tang, JCA van der Lubbe, M Loog
Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation …, 2016
22016
Depth estimation based on ego-motion estimation and residual flow estimation
J Tang, RA Ambrus, V Guizilini, AD Gaidon
US Patent App. 17/230,941, 2021
12021
Semantically aware keypoint matching
J Tang, RA Ambrus, V Guizilini, AD Gaidon
US Patent App. 17/230,947, 2021
12021
Incremental map building using learnable features and descriptors
J Tang, RA Ambrus, H Kim, V Guizilini, AD Gaidon, W Xipeng, J WALLS, ...
US Patent App. 17/230,942, 2021
12021
Systems and methods for training a neural keypoint detection network
J Tang, RA Ambrus, V Guizilini, S Pillai, H Kim
US Patent 11,256,986, 2022
2022
Multi-view depth estimation leveraging offline structure-from-motion
J Tang, RA Ambrus, S Pillai, V Guizilini, AD Gaidon
US Patent App. 17/368,703, 2022
2022
Self-supervised 3d keypoint learning for ego-motion estimation
J Tang, RA Ambrus, V Guizilini, S Pillai, H Kim, AD Gaidon
US Patent App. 17/093,360, 2021
2021
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