Ning Qiang

According to our database, Ning Qiang authored at least 28 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

An Explainable and Generalizable Recurrent Neural Network Approach for Differentiating Human Brain States on EEG Dataset.

Shu Zhang, Lin Wu, Sigang Yu, Enze Shi, Ning Qiang, Huan Gao, Jingyi Zhao, Shijie Zhao

IEEE Trans. Neural Networks Learn. Syst., June, 2024

Spatial-temporal convolutional attention for discovering and characterizing functional brain networks in task fMRI.

Yiheng Liu, Enjie Ge, Zili Kang, Ning Qiang, Tianming Liu, Bao Ge

NeuroImage, February, 2024

End-to-End Prediction of EGFR Mutation Status With Denseformer.

Shijie Zhao, Wenyuan Li, Zhuoyan Liu, Tianji Pang, Yang Yang, Ning Qiang, Jingyi Zhao, Bangguo Li, Baiying Lei, Junwei Han

IEEE J. Biomed. Health Informatics, January, 2024

A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks.

Jiaqi Wang, Hanqi Jiang, Yiheng Liu, Chong Ma, Xu Zhang, Yi Pan, Mengyuan Liu, Peiran Gu, Sichen Xia, Wenjun Li, Yutong Zhang, Zihao Wu, Zhengliang Liu, Tianyang Zhong, Bao Ge, Tuo Zhang, Ning Qiang, Xintao Hu, Xi Jiang, Xin Zhang, Wei Zhang, Dinggang Shen, Tianming Liu, Shu Zhang

CoRR, 2024

Understanding LLMs: A Comprehensive Overview from Training to Inference.

Yiheng Liu, Hao He, Tianle Han, Xu Zhang, Mengyuan Liu, Jiaming Tian, Yutong Zhang, Jiaqi Wang, Xiaohui Gao, Tianyang Zhong, Yi Pan, Shaochen Xu, Zihao Wu, Zhengliang Liu, Xin Zhang, Shu Zhang, Xintao Hu, Tuo Zhang, Ning Qiang, Tianming Liu, Bao Ge

CoRR, 2024

Deep Linear Matrix Approximate Reconstruction Reveals Reproducible Large-Scale Functional Connectivity Networks in the Human Brain.

Wei Zhang, Xi Jiang, Shijie Zhao, Ning Qiang, Yu Bao, Jinglei Lv

Proceedings of the 1st International Workshop on Multimedia Computing for Health and Medicine, 2024

2023

Functional brain network identification and fMRI augmentation using a VAE-GAN framework.

Ning Qiang, Jie Gao, Qinglin Dong, Huiji Yue, Hongtao Liang, Lili Liu, Jingjing Yu, Jing Hu, Shu Zhang, Bao Ge, Yifei Sun, Zhengliang Liu, Tianming Liu, Jin Li, Hujie Song, Shijie Zhao

Comput. Biol. Medicine, October, 2023

Holistic Evaluation of GPT-4V for Biomedical Imaging.

Zhengliang Liu, Hanqi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yiwei Li, Xiaowei Yu, Yutong Zhang, Yi Pan, Peng Shu, Yanjun Lyu, Lu Zhang, Junjie Yao, Peixin Dong, Chao Cao, Zhenxiang Xiao, Jiaqi Wang, Huan Zhao, Shaochen Xu, Yaonai Wei, Jingyuan Chen, Haixing Dai, Peilong Wang, Hao He, Zewei Wang, Xinyu Wang, Xu Zhang, Lin Zhao, Yiheng Liu, Kai Zhang, Liheng Yan, Lichao Sun, Jun Liu, Ning Qiang, Bao Ge, Xiaoyan Cai, Shijie Zhao, Xintao Hu, Yixuan Yuan, Gang Li, Shu Zhang, Xin Zhang, Xi Jiang, Tuo Zhang, Dinggang Shen, Quanzheng Li, Wei Liu, Xiang Li, Dajiang Zhu, Tianming Liu

CoRR, 2023

Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models.

Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Dajiang Zhu, Xiang Li, Ning Qiang, Dinggang Shen, Tianming Liu, Bao Ge

CoRR, 2023

Spatial-Temporal Convolutional Attention for Mapping Functional Brain Networks.

Yiheng Liu, Enjie Ge, Ning Qiang, Tianming Liu, Bao Ge

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022

A novel ADHD classification method based on resting state temporal templates (RSTT) using spatiotemporal attention auto-encoder.

Ning Qiang, Qinglin Dong, Hongtao Liang, Bao Ge, Shu Zhang, Cheng Zhang, Jie Gao, Yifei Sun

Neural Comput. Appl., 2022

Learning brain representation using recurrent Wasserstein generative adversarial net.

Ning Qiang, Qinglin Dong, Hongtao Liang, Jin Li, Shu Zhang, Cheng Zhang, Bao Ge, Yifei Sun, Jie Gao, Tianming Liu, Huiji Yue, Shijie Zhao

Comput. Methods Programs Biomed., 2022

Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner.

Zhenwei Wang, Yifan Lv, Mengshen He, Enjie Ge, Ning Qiang, Bao Ge

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Multi-head Attention-Based Masked Sequence Model for Mapping Functional Brain Networks.

Mengshen He, Xiangyu Hou, Zhenwei Wang, Zili Kang, Xin Zhang, Ning Qiang, Bao Ge

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Deep Variational Autoencoder for Mapping Functional Brain Networks.

Ning Qiang, Qinglin Dong, Fangfei Ge, Hongtao Liang, Bao Ge, Shu Zhang, Yifei Sun, Jie Gao, Tianming Liu

IEEE Trans. Cogn. Dev. Syst., 2021

A novel framework based on wavelet transform and principal component for face recognition under varying illumination.

Hongtao Liang, Jie Gao, Ning Qiang

Appl. Intell., 2021

2020

Modeling Hierarchical Brain Networks via Volumetric Sparse Deep Belief Network.

Qinglin Dong, Fangfei Ge, Ning Qiang, Yu Zhao, Jinglei Lv, Heng Huang, Jing Yuan, Xi Jiang, Dinggang Shen, Tianming Liu

IEEE Trans. Biomed. Eng., 2020

Modeling task-based fMRI data via deep belief network with neural architecture search.

Ning Qiang, Qinglin Dong, Wei Zhang, Bao Ge, Fangfei Ge, Hongtao Liang, Yifei Sun, Jie Gao, Tianming Liu

Comput. Medical Imaging Graph., 2020

A Behavior-Driven Coordination Control Framework for Target Hunting by UUV Intelligent Swarm.

Hongtao Liang, Yanfang Fu, Fengju Kang, Jie Gao, Ning Qiang

IEEE Access, 2020

Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification.

Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Tianming Liu, Quanzheng Li

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE).

Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Tianming Liu, Quanzheng Li

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

A Novel fMRI Representation Learning Framework with GAN.

Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Liang Dong, Tianming Liu, Quanzheng Li

Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

Task fMRI Guided Fiber Clustering via a Deep Clustering Method.

Huan Wang, Qinglin Dong, Ning Qiang, Xin Zhang, Tianming Liu, Bao Ge

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Deep Variational Autoencoder for Modeling Functional Brain Networks and ADHD Identification.

Ning Qiang, Qinglin Dong, Yifei Sun, Bao Ge, Tianming Liu

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019

Neural Architecture Search for Optimizing Deep Belief Network Models of fMRI Data.

Ning Qiang, Bao Ge, Qinglin Dong, Fangfei Ge, Tianming Liu

Proceedings of the Multiscale Multimodal Medical Imaging - First International Workshop, 2019

Simultaneous Spatial-Temporal Decomposition of Connectome-Scale Brain Networks by Deep Sparse Recurrent Auto-Encoders.

Qing Li, Qinglin Dong, Fangfei Ge, Ning Qiang, Yu Zhao, Han Wang, Heng Huang, Xia Wu, Tianming Liu

Proceedings of the Information Processing in Medical Imaging, 2019

2018

Multi-objective Optimized Noise Reduction Design of Complicated Structure-Borne Acoustic Radiation Under Multiple Constrains.

Jie Gao, Ning Qiang

Wirel. Pers. Commun., 2018

Multi-objective Optimized Design for Intermediate-Frequency Noise Reduction in Aircraft Cabins.

Jie Gao, Ning Qiang

Wirel. Pers. Commun., 2018