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ORCIDKangning Liu
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2020 – today
- 2024
[j5]Liuliu Xu, Dingqiang Fan
, Kangning Liu, Wangyang Xu, Rui Yu:
A machine learning framework for intelligent development of Ultra-High performance concrete (UHPC): From dataset cleaning to performance predicting. Expert Syst. Appl. 242: 122790 (2024)- [j4]Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda:
Quantifying impairment and disease severity using AI models trained on healthy subjects. npj Digit. Medicine 7(1) (2024) - [j3]Jianyao Jia, Guofeng Ma, Hongyang Li, Jiyong Ding, Kangning Liu:
Social Power Antecedents of Knowledge Sharing in Project-Oriented Online Communities. IEEE Trans. Engineering Management 71: 2493-2505 (2024) - 2023
- [j2]Jinglian Tian, Yongzhong Tian, Yan Cao, Wenhao Wan, Kangning Liu:
Research on Rice Fields Extraction by NDVI Difference Method Based on Sentinel Data. Sensors 23(13): 5876 (2023) - [c6]Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda:
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CVPR 2023: 3355-3365 - [i10]Kangning Liu, Yu-Chuan Su, Wei Hong, Ruijin Cang, Xuhui Jia:
Controllable One-Shot Face Video Synthesis With Semantic Aware Prior. CoRR abs/2304.14471 (2023) - [i9]Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi M. Schambra, Carlos Fernandez-Granda:
Quantifying Impairment and Disease Severity Using AI Models Trained on Healthy Subjects. CoRR abs/2311.12781 (2023) - 2022
- [c5]Sheng Liu, Kangning Liu, Weicheng Zhu, Yiqiu Shen, Carlos Fernandez-Granda:
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations. CVPR 2022: 2596-2606 - [c4]Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda:
StrokeRehab: A Benchmark Dataset for Sub-second Action Identification. NeurIPS 2022 - [c3]Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu:
Are All Losses Created Equal: A Neural Collapse Perspective. NeurIPS 2022 - [i8]Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu:
Are All Losses Created Equal: A Neural Collapse Perspective. CoRR abs/2210.02192 (2022) - [i7]Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda:
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CoRR abs/2210.09452 (2022) - 2021
- [j1]Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Kangning Liu, Sudarshini Tyagi, Laura Heacock, Sungheon Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. Medical Image Anal. 68: 101908 (2021) - [c2]Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Piotr Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras:
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis. MIDL 2021: 451-472 - [c1]Kangning Liu, Shuhang Gu, Andrés Romero, Radu Timofte:
Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning. WACV 2021: 1029-1039 - [i6]Kangning Liu, Yiqiu Shen, Nan Wu, Jakub Chledowski, Carlos Fernandez-Granda, Krzysztof J. Geras:
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis. CoRR abs/2106.07049 (2021) - [i5]Xiaoxia Zhang, Quentin Duchemin, Kangning Liu, Sebastian Flassbeck, Cem Gultekin, Carlos Fernandez-Granda, Jakob Assländer:
Cramér-Rao bound-informed training of neural networks for quantitative MRI. CoRR abs/2109.10535 (2021) - [i4]Sheng Liu, Kangning Liu, Weicheng Zhu, Yiqiu Shen, Carlos Fernandez-Granda:
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations. CoRR abs/2110.03740 (2021) - [i3]Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda:
Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution. CoRR abs/2111.02521 (2021) - 2020
- [i2]Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Kangning Liu, Sudarshini Tyagi, Laura Heacock, Sungheon Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. CoRR abs/2002.07613 (2020) - [i1]Kangning Liu, Shuhang Gu, Andrés Romero, Radu Timofte:
Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning. CoRR abs/2004.06502 (2020)
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