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Jiexiong Tang
Jiexiong Tang
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Zitiert von
Zitiert von
Jahr
Extreme learning machine for multilayer perceptron
J Tang, C Deng, GB Huang
IEEE Transactions on Neural Networks and Learning Systems, 2015
14772015
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
4572014
Extreme learning machines: new trends and applications
CW Deng, GB Huang, J Xu, JX Tang
Science China. Information Sciences 58 (2), 1-16, 2015
1542015
GCNv2: Efficient Correspondence Prediction for Real-Time SLAM
J Tang, L Ericson, J Folkesson, P Jensfelt
arXiv:1902.11046, 2019
1382019
Geometric correspondence network for camera motion estimation
J Tang, J Folkesson, P Jensfelt
IEEE Robotics and Automation Letters 3 (2), 1010-1017, 2018
652018
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
292021
Neural outlier rejection for self-supervised keypoint learning
J Tang, H Kim, V Guizilini, S Pillai, R Ambrus
arXiv preprint arXiv:1912.10615, 2019
292019
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
292014
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
152019
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
32022
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
32021
Self-supervised 3D keypoint learning for ego-motion estimation
J Tang, RA Ambrus, V Guizilini, S Pillai, H Kim, AD Gaidon
US Patent 11,900,626, 2024
22024
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
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
Semantically aware keypoint matching
J Tang, RA Ambrus, V Guizilini, AD Gaidon
US Patent App. 18/489,687, 2024
2024
Semantically aware keypoint matching
J Tang, RA Ambrus, V Guizilini, AD Gaidon
US Patent 11,830,253, 2023
2023
Depth estimation based on ego-motion estimation and residual flow estimation
J Tang, RA Ambrus, V Guizilini, AD Gaidon
US Patent App. 18/344,700, 2023
2023
Keypoint matching using graph convolutions
J Tang, RA Ambrus, J Li, V Guizilini, S Pillai, AD Gaidon
US Patent 11,741,728, 2023
2023
Depth estimation based on ego-motion estimation and residual flow estimation
J Tang, RA Ambrus, V Guizilini, AD Gaidon
US Patent 11,727,588, 2023
2023
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
2022
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