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Simultaneously Calibration of Multi Hand-Eye Robot System Based on Graph 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2023, 卷号: 71, 期号: 5, 页码: 5010-5020
作者:  Zhou, Zishun;  Ma, Liping;  Liu, Xilong;  Cao, Zhiqiang;  Yu, Junzhi
收藏  |  浏览/下载：31/0  |  提交时间：2024/03/26
Calibration  error correction  graph theory  multirobot systems  robot vision systems.  
Simultaneously Calibration of Multi HandEye Robot System Based on Graph 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 卷号: 71, 期号: 5, 页码: 5010-5020
作者:  Zhou, Zishun;  Ma, Liping;  Liu, Xilong;  Cao, Zhiqiang;  Yu, Junzhi
收藏  |  浏览/下载：80/0  |  提交时间：2024/02/20
Calibration  error correction  graph theory  multirobot systems  robot vision systems  
Semantic-Context Graph Network for Point-Based 3D Object Detection 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 11, 页码: 6474-6486
作者:  Dong, Shuwei;  Kong, Xiaoyu;  Pan, Xingjia;  Tang, Fan;  Li, Wei;  Chang, Yi;  Dong, Weiming
收藏  |  浏览/下载：112/0  |  提交时间：2023/12/21
3D object detection  graph neural networks  information entanglement  
Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images 期刊论文
RHEUMATOLOGY, 2023, 页码: 8
作者:  He, Xuelei;  Wang, Ming;  Zhao, Chenyang;  Wang, Qian;  Zhang, Rui;  Liu, Jian;  Zhang, Yixiu;  Qi, Zhenhong;  Su, Na;  Wei, Yao;  Gui, Yang;  Li, Jianchu;  Tian, Xinping;  Zeng, Xiaofeng;  Jiang, Yuxin;  Wang, Kun;  Yang, Meng
收藏  |  浏览/下载：115/0  |  提交时间：2023/11/17
deep learning  RA  activity  scoring  multimodal ultrasonography  
Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer 期刊论文
MEDICAL PHYSICS, 2023, 页码: 11
作者:  Liu, Shengyuan;  Deng, Jingyu;  Dong, Di;  Fang, Mengjie;  Ye, Zhaoxiang;  Hu, Yanfeng;  Li, Hailin;  Zhong, Lianzhen;  Cao, Runnan;  Zhao, Xun;  Shang, Wenting;  Li, Guoxin;  Liang, Han;  Tian, Jie
收藏  |  浏览/下载：143/0  |  提交时间：2023/11/17
deep learning  extranodal soft tissue metastasis  gastric cancer  radiomics  
Zero-Shot Predicate Prediction for Scene Graph Parsing 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 3140-3153
作者:  Li, Yiming;  Yang, Xiaoshan;  Huang, Xuhui;  Ma, Zhe;  Xu, Changsheng
收藏  |  浏览/下载：145/0  |  提交时间：2023/11/17
Deep learning  zero-shot  scene graph  
Development and Testing of Advanced Driver Assistance Systems Through Scenario-Based Systems Engineering 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 卷号: 8, 期号: 8, 页码: 3968-3973
作者:  Li, Xuan;  Song, Rui;  Fan, Junfeng;  Liu, Mingyang;  Wang, Fei-Yue
收藏  |  浏览/下载：164/0  |  提交时间：2023/11/16
Roads  Testing  Vehicles  Systems engineering and theory  Advanced driver assistance systems  Meters  Autonomous vehicles  Scenarios-based system engineering  advanced driver assistance systems  parallel intelligence  lane keeping assistance  adaptive cruise control  autonomous emergency braking  
Cross-Architecture Knowledge Distillation 会议论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, Macau SAR, China, 2022.12.4-2022.12.8
作者:  Yufan Liu;  Jiajiong Cao;  Bing Li;  Weiming Hu;  Jingting Ding;  Liang Li
Adobe PDF(1020Kb)  |  收藏  |  浏览/下载：149/43  |  提交时间：2023/04/23
Knowledge distillation  Cross architecture  Model compression  Deep learning  
Rethinking Pretraining as a Bridge From ANNs to SNNs 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 14
作者:  Lin, Yihan;  Hu, Yifan;  Ma, Shijie;  Yu, Dongjie;  Li, Guoqi
收藏  |  浏览/下载：264/0  |  提交时间：2023/03/20
Training  Task analysis  Neurons  Pipelines  Artificial neural networks  Feature extraction  Transfer learning  Event-driven dataset  neural network (NN) analysis  pretraining technique  spiking NN (SNN)  transfer learning  
Discrete soft actor-critic with auto-encoder on vascular robotic system 期刊论文
ROBOTICA, 2022, 页码: 12
作者:  Li, Hao;  Zhou, Xiao-Hu;  Xie, Xiao-Liang;  Liu, Shi-Qi;  Gui, Mei-Jiang;  Xiang, Tian-Yu;  Wang, Jin-Li;  Hou, Zeng-Guang
收藏  |  浏览/下载：242/0  |  提交时间：2023/01/09
surgical robots  vascular robotic system  automation  reinforcement learning  deep neural network