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IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection Conference paper
Yin, Junbo, Shen, Jianbing, Chen, Runnan, Li, Wei, Yang, Ruigang, Frossard, Pascal, Wang, Wenguan. IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection[C]:IEEE Computer Society, 2024, 14905-14915.
Authors:  Yin, Junbo;  Shen, Jianbing;  Chen, Runnan;  Li, Wei;  Yang, Ruigang; et al.
Favorite | TC[Scopus]:3 | Submit date：2024/11/05
Point Cloud Compression  Computer Vision  Three-dimensional Displays  Collaboration  Object Detection  Benchmark Testing  Transformers  Multimodal  Object Detection  Point Cloud  Autonomous Driving  
SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud Conference paper
Wang, Yan, Yin, Junbo, Li, Wei, Frossard, Pascal, Yang, Ruigang, Shen, Jianbing. SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud[C]:AAAI Press, 2023, 2707-2715.
Authors:  Wang, Yan;  Yin, Junbo;  Li, Wei;  Frossard, Pascal;  Yang, Ruigang; et al.
Favorite | TC[Scopus]:21 | Submit date：2023/09/27
ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection Conference paper
Yin, Junbo, Zhou, Dingfu, Zhang, Liangjun, Fang, Jin, Xu, Cheng Zhong, Shen, Jianbing, Wang, Wenguan. ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2022, 17-33.
Authors:  Yin, Junbo;  Zhou, Dingfu;  Zhang, Liangjun;  Fang, Jin;  Xu, Cheng Zhong; et al.
Favorite | TC[WOS]:33 TC[Scopus]:48 | Submit date：2023/01/30
3d Object Detection  Unsupervised Point Cloud Pre-training  
Semi-supervised 3D Object Detection with Proficient Teachers Conference paper
Yin, Junbo, Fang, Jin, Zhou, Dingfu, Zhang, Liangjun, Xu, Cheng Zhong, Shen, Jianbing, Wang, Wenguan. Semi-supervised 3D Object Detection with Proficient Teachers[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2022, 727-743.
Authors:  Yin, Junbo;  Fang, Jin;  Zhou, Dingfu;  Zhang, Liangjun;  Xu, Cheng Zhong; et al.
Favorite | TC[WOS]:35 TC[Scopus]:47 | Submit date：2023/01/30
3d Object Detection  Point Cloud  Semi-supervised Learning  
ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection Conference paper
Junbo, Yin, Junbo, Yin, Liangjun, Zhang, Jin, Fang, Dingfu, Zhou, Cheng-Zhong, Xu, Jianbing, Shen, Wenguan, Wang. ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection[C], 2022.
Authors:  Junbo, Yin;  Junbo, Yin;  Liangjun, Zhang;  Jin, Fang;  Dingfu, Zhou; et al.
Favorite | TC[WOS]:33 TC[Scopus]:48 | Submit date：2023/08/08
3d Object Detection  Unsupervised Point Cloud Pre-training  
Semi-supervised 3D Object Detection with Proficient Teachers Conference paper
Junbo, Yin, Jin, Fang, Dingfu, Zhou, Liangjun, Zhang, Cheng-Zhong, Xu, Jianbing, Shen, Wenguan, Wang. Semi-supervised 3D Object Detection with Proficient Teachers[C], 2022.
Authors:  Junbo, Yin;  Jin, Fang;  Dingfu, Zhou;  Liangjun, Zhang;  Cheng-Zhong, Xu; et al.
Favorite | TC[WOS]:35 TC[Scopus]:47 | Submit date：2023/08/08
3d Object Detection  Semi-supervised Learning  Point Cloud  
Shortening passengers' travel time: A dynamic metro train scheduling approach using deep reinforcement learning Journal article
Wang, Zhaoyuan, Pan, Zheyi, Chen, Shun, Ji, Shenggong, Yi, Xiuwen, Zhang, Junbo, Wang, Jingyuan, Gong, Zhiguo, Li, Tianrui, Zheng, Yu. Shortening passengers' travel time: A dynamic metro train scheduling approach using deep reinforcement learning[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 35(5), 5282-5295.
Authors:  Wang, Zhaoyuan;  Pan, Zheyi;  Chen, Shun;  Ji, Shenggong;  Yi, Xiuwen; et al.
Favorite | TC[WOS]:1 TC[Scopus]:3  IF:8.9/8.8 | Submit date：2022/05/17
Metro Systems  Spatio-temporal Data  Neural Network  Deep Reinforcement Learning  Urban Computing  
Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements Journal article
Zhou, Kai, Sun, Yaoting, Li, Lu, Zang, Zelin, Wang, Jing, Li, Jun, Liang, Junbo, Zhang, Fangfei, Zhang, Qiushi, Ge, Weigang, Chen, Hao, Sun, Xindong, Yue, Liang, Wu, Xiaomai, Shen, Bo, Xu, Jiaqin, Zhu, Hongguo, Chen, Shiyong, Yang, Hai, Huang, Shigao, Peng, Minfei, Lv, Dongqing, Zhang, Chao, Zhao, Haihong, Hong, Luxiao, Zhou, Zhehan, Chen, Haixiao, Dong, Xuejun, Tu, Chunyu, Li, Minghui, Zhu, Yi, Chen, Baofu, Li, Stan Z., Guo, Tiannan. Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements[J]. Computational and Structural Biotechnology Journal, 2021, 19, 3640-3649.
Authors:  Zhou, Kai;  Sun, Yaoting;  Li, Lu;  Zang, Zelin;  Wang, Jing; et al.
Favorite | TC[WOS]:26 TC[Scopus]:29  IF:4.4/5.0 | Submit date：2021/12/07
Covid-19  Sars-cov-2  Severity Prediction  Machine Learning  Routine Clinical Test  Longitudinal Dynamics  
Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms Journal article
Hang Yang, Simon Fong, Kyungeun Cho, Junbo Wang. Atmospheric pattern recognition of human activities on ubiquitous sensor network using data stream mining algorithms[J]. International Journal of Sensor Networks, 2016, 20(3), 147-162.
Authors:  Hang Yang;  Simon Fong;  Kyungeun Cho;  Junbo Wang
Favorite | TC[WOS]:5 TC[Scopus]:6  IF:1.1/0.8 | Submit date：2019/02/13
Atmospheric Pattern Recognition  Ubiquitous Sensor Networks  Data Stream Mining  Data Mining  Atmospheric Measurements  Indoor Networks  Human Activities  Streaming Sensor Data  Model Induction  Rule Extraction  Environmental Sensing  Decision Support Centres