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2020 – today
- 2025
[j31]Feng Luo, Weixin Bian, Biao Jie, Haotong Dong, Xinglin Fu:
ARBFPN-YOLOv8: auxiliary reversible bidirectional feature pyramid network for UAV small target detection. Signal Image Video Process. 19(1): 63 (2025)- 2024
- [j30]Chen Wang
, Kaizhong Zuo, Shaokun Zhang, Chunyang Liu, Hao Peng, Wenjie Li, Zhangyi Shen, Peng Hu, Rui Wang, Biao Jie:
TADGCN: A Time-Aware Dynamic Graph Convolution Network for long-term traffic flow prediction. Expert Syst. Appl. 258: 125134 (2024) - [j29]Xintao Ding, Yonglong Luo, Biao Jie, Qingde Li, Yongqiang Cheng:
Using outlier elimination to assess learning-based correspondence matching methods. Inf. Sci. 659: 120056 (2024) - [j28]Lifang Zhu, Chao Liu, Zhiqiang Zhang, Yifan Cheng, Biao Jie, Xintao Ding:
An adversarial sample detection method based on heterogeneous denoising. Mach. Vis. Appl. 35(4): 96 (2024) - [j27]Yi Huang, Weixin Bian, Biao Jie, Zhiqiang Zhu, Wenhu Li:
Image super-resolution reconstruction based on deep dictionary learning and A+. Signal Image Video Process. 18(3): 2629-2641 (2024) - [j26]Yi Huang, Weixin Bian, Deqin Xu, Biao Jie, Luo Feng:
Fingerprint image super-resolution based on multi-class deep dictionary learning and ridge prior. Signal Image Video Process. 18(6-7): 5491-5501 (2024) - [j25]Jie Zhou, Biao Jie, Zhengdong Wang, Zhixiang Zhang, Tongchun Du, Weixin Bian, Yang Yang, Jun Jia:
LCGNet: Local Sequential Feature Coupling Global Representation Learning for Functional Connectivity Network Analysis With fMRI. IEEE Trans. Medical Imaging 43(12): 4319-4330 (2024) - [c30]Jie Zhou, Biao Jie, Zhengdong Wang, Zhixiang Zhang, Wei Shao, Weixin Bian, Yang Yang, Tongchun Du:
Double Collaborative Learning on Functional Brain Networks for Brain Disease Classification. ISBI 2024: 1-5 - [c29]Zhaoxiang Wu, Biao Jie, Wen Li, Wentao Jiang, Yang Yang, Tongchun Du:
Structural-Connectivity-Guided Functional Connectivity Representation for Multi-modal Brain Disease Classification. MLMI@MICCAI (1) 2024: 156-165 - 2023
- [c28]Yi Huang, Weixin Bian, Biao Jie, Zhiqiang Zhu, Wenhu Li:
Image Super-Resolution via Deep Dictionary Learning. ICIG (4) 2023: 21-32 - [c27]Xingyu Zhang, Biao Jie, Jianhui Wang:
Convolutional Recurrent Neural Network with Multi-Scale Kernels on Dynamic Connectivity Network for AD Classification. ICMLSC 2023: 69-74 - [c26]Jianhui Wang, Biao Jie, Xingyu Zhang, Wen Li, Zhaoxiang Wu, Yang Yang:
Sparse-learning-based High-order Dynamic Functional Connectivity Networks for Brain Disease Classification. ICMLSC 2023: 161-167 - [c25]Jie Zhou, Biao Jie, Zhengdong Wang, Zhixiang Zhang, Weixin Bian, Yang Yang:
Local Sequential Features Coupling Global Representation of Dynamic Functional Connectivity Network for Brain Disease Classification. ISBI 2023: 1-5 - [c24]Yang Shu, Wanggen Li, Doudou Li, Kun Gao, Biao Jie:
Multi-scale Dilated Attention Graph Convolutional Network for Skeleton-Based Action Recognition. PRCV (1) 2023: 16-28 - 2022
- [j24]Hui Zhang, Weixin Bian, Biao Jie, Shuwan Sun:
BioP-TAP: An efficient method of template protection and two-factor authentication protocol combining biometric and PUF. J. Intell. Fuzzy Syst. 43(4): 4317-4333 (2022) - [j23]Wen Zhou, Wenying Jiang, Biao Jie, Weixin Bian:
Multiagent evacuation framework for a virtual fire emergency scenario based on generative adversarial imitation learning. Comput. Animat. Virtual Worlds 33(1) (2022) - [j22]Zhengdong Wang, Biao Jie, Chunxiang Feng, Taochun Wang, Weixin Bian, Xintao Ding, Wen Zhou, Mingxia Liu:
Distribution-Guided Network Thresholding for Functional Connectivity Analysis in fMRI-Based Brain Disorder Identification. IEEE J. Biomed. Health Informatics 26(4): 1602-1613 (2022) - [c23]Zhixiang Zhang, Biao Jie, Zhengdong Wang, Jie Zhou, Yang Yang:
Self-attention Based High Order Sequence Features of Dynamic Functional Connectivity Networks with rs-fMRI for Brain Disease Classification. CICAI (2) 2022: 626-637 - [i2]Zhixiang Zhang, Biao Jie, Zhengdong Wang, Jie Zhou, Yang Yang:
Self-attention based high order sequence feature reconstruction of dynamic functional connectivity networks with rs-fMRI for brain disease classification. CoRR abs/2211.11750 (2022) - 2021
- [j21]Ming Zheng, Tong Li, Liping Sun, Taochun Wang, Biao Jie, Weiyi Yang, Mingjing Tang, Changlong Lv:
An automatic sampling ratio detection method based on genetic algorithm for imbalanced data classification. Knowl. Based Syst. 216: 106800 (2021) - [j20]Hui Zhang, Weixin Bian, Biao Jie, Deqin Xu, Jun Zhao:
A Complete User Authentication and Key Agreement Scheme Using Cancelable Biometrics and PUF in Multi-Server Environment. IEEE Trans. Inf. Forensics Secur. 16: 5413-5428 (2021) - [c22]Hui Zhang, Weixin Bian, Biao Jie, Shuwan Sun:
A Novel Method of Template Protection and Two-Factor Authentication Protocol Based on Biometric and PUF. CSS 2021: 97-106 - [c21]Kai Lin, Biao Jie, Peng Dong, Xintao Ding, Weixin Bian, Mingxia Liu:
Extracting Sequential Features from Dynamic Connectivity Network with rs-fMRI Data for AD Classification. MLMI@MICCAI 2021: 664-673 - [c20]Peng Dong, Biao Jie, Lin Kai, Xintao Ding, Weixin Bian, Mingxia Liu:
Integration of Handcrafted and Embedded Features from Functional Connectivity Network with rs-fMRI forBrain Disease Classification. MLMI@MICCAI 2021: 674-681 - 2020
- [j19]Jun Zhao, Weixin Bian, Deqin Xu, Biao Jie, Xintao Ding, Wen Zhou, Hui Zhang:
A Secure Biometrics and PUFs-Based Authentication Scheme With Key Agreement For Multi-Server Environments. IEEE Access 8: 45292-45303 (2020) - [j18]Xintao Ding, Qingde Li, Yongqiang Cheng, Jinbao Wang, Weixin Bian, Biao Jie:
Local keypoint-based Faster R-CNN. Appl. Intell. 50(10): 3007-3022 (2020) - [j17]Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen:
Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis. Medical Image Anal. 63: 101709 (2020) - [j16]Jiashuang Huang, Mingliang Wang, Xijia Xu, Biao Jie, Daoqiang Zhang:
A novel node-level structure embedding and alignment representation of structural networks for brain disease analysis. Medical Image Anal. 65: 101755 (2020) - [c19]Chunxiang Feng, Biao Jie, Xintao Ding, Daoqiang Zhang, Mingxia Liu:
Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification. MLMI@MICCAI 2020: 303-311 - [i1]Kai Ma, Biao Jie, Wei Shao, Daoqiang Zhang:
Ordinal Pattern Kernel for Brain Connectivity Network Classification. CoRR abs/2008.07719 (2020)
2010 – 2019
- 2019
- [j15]Weixin Bian, Deqin Xu, Qingde Li, Yongqiang Cheng, Biao Jie, Xintao Ding:
A Survey of the Methods on Fingerprint Orientation Field Estimation. IEEE Access 7: 32644-32663 (2019) - [j14]Mi Wang, Biao Jie, Weixin Bian, Xintao Ding, Wen Zhou, Zhengdong Wang, Mingxia Liu:
Graph-Kernel Based Structured Feature Selection for Brain Disease Classification Using Functional Connectivity Networks. IEEE Access 7: 35001-35011 (2019) - [j13]Wen Zhou, Fei Chen, Yongshuo Zong, Dadong Zhao, Biao Jie, Zhengdong Wang, Chenxi Huang, Eddie-Yin-Kwee Ng:
Automatic Detection Approach for Bioresorbable Vascular Scaffolds Using a U-Shaped Convolutional Neural Network. IEEE Access 7: 94424-94430 (2019) - [j12]Wen Zhou, Wenying Jiang, Weixin Bian, Biao Jie:
Webvr Human-Centered Indoor Layout Design Framework Using a Convolutional Neural Network and Deep Q-Learning. IEEE Access 7: 185773-185785 (2019) - [j11]Yang Li, Jingyu Liu, Xinqiang Gao, Biao Jie, Minjeong Kim, Pew-Thian Yap, Chong-Yaw Wee, Dinggang Shen:
Multimodal hyper-connectivity of functional networks using functionally-weighted LASSO for MCI classification. Medical Image Anal. 52: 80-96 (2019) - [c18]Zhengdong Wang, Biao Jie, Weixin Bian, Daoqiang Zhang, Dinggang Shen, Mingxia Liu:
Adaptive Thresholding of Functional Connectivity Networks for fMRI-Based Brain Disease Analysis. GLMI@MICCAI 2019: 18-26 - [c17]Zhengdong Wang, Biao Jie, Mi Wang, Chunxiang Feng, Wen Zhou, Dinggang Shen, Mingxia Liu:
Graph-Kernel-Based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification. GLMI@MICCAI 2019: 27-35 - [e1]Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu:
Graph Learning in Medical Imaging - First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11849, Springer 2019, ISBN 978-3-030-35816-7 [contents] - 2018
- [j10]Biao Jie, Mingxia Liu, Dinggang Shen:
Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease. Medical Image Anal. 47: 81-94 (2018) - [j9]Biao Jie, Mingxia Liu, Daoqiang Zhang, Dinggang Shen:
Sub-Network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis. IEEE Trans. Image Process. 27(5): 2340-2353 (2018) - [j8]Daoqiang Zhang, Jiashuang Huang, Biao Jie, Junqiang Du, Liyang Tu, Mingxia Liu:
Ordinal Pattern: A New Descriptor for Brain Connectivity Networks. IEEE Trans. Medical Imaging 37(7): 1711-1722 (2018) - [c16]Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen:
Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarchical Functional Connectivities from fMRI for Disease Diagnosis. MLMI@MICCAI 2018: 1-9 - 2017
- [j7]Biao Jie, Mingxia Liu, Jun Liu, Daoqiang Zhang, Dinggang Shen:
Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease. IEEE Trans. Biomed. Eng. 64(1): 238-249 (2017) - [c15]Yang Li, Xinqiang Gao, Biao Jie, Pew-Thian Yap, Minjeong Kim, Chong-Yaw Wee, Dinggang Shen:
Multimodal Hyper-connectivity Networks for MCI Classification. MICCAI (1) 2017: 433-441 - 2016
- [j6]Junqiang Du, Lipeng Wang, Biao Jie, Daoqiang Zhang:
Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA. Comput. Medical Imaging Graph. 52: 82-88 (2016) - [j5]Xintao Ding, Yonglong Luo, Yunyun Yi, Biao Jie, Taochun Wang, Weixin Bian:
Orthogonal design for scale invariant feature transform optimization. J. Electronic Imaging 25(5): 053030 (2016) - [j4]Biao Jie, Chong-Yaw Wee, Dinggang Shen, Daoqiang Zhang:
Hyper-connectivity of functional networks for brain disease diagnosis. Medical Image Anal. 32: 84-100 (2016) - [c14]Biao Jie, Mingxia Liu, Xi Jiang, Daoqiang Zhang:
Sub-network Based Kernels for Brain Network Classification. BCB 2016: 622-629 - [c13]Fengjun Zhao, Yanrong Chen, Huangjian Yi, Xiaowei He, Biao Jie:
Vessel Extraction by Graph Cut Method based on Centerline Estimation. ICIMCS 2016: 234-237 - [c12]Mingxia Liu, Junqiang Du, Biao Jie, Daoqiang Zhang:
Ordinal Patterns for Connectivity Networks in Brain Disease Diagnosis. MICCAI (1) 2016: 1-9 - 2015
- [c11]Tingting Ye, Chen Zu, Biao Jie, Dinggang Shen, Daoqiang Zhang:
Discriminative Multi-task Feature Selection for Multi-modality Based AD/MCI Classification. PRNI 2015: 45-48 - 2014
- [j3]Fei Fei, Biao Jie, Daoqiang Zhang:
Frequent and Discriminative Subnetwork Mining for Mild Cognitive Impairment Classification. Brain Connect. 4(5): 347-360 (2014) - [j2]Yang Li, Chong-Yaw Wee, Biao Jie, Zi-Wen Peng, Dinggang Shen:
Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification. Neuroinformatics 12(3): 455-469 (2014) - [j1]Biao Jie, Daoqiang Zhang, Wei Gao, Qian Wang, Chong-Yaw Wee, Dinggang Shen:
Integration of Network Topological and Connectivity Properties for Neuroimaging Classification. IEEE Trans. Biomed. Eng. 61(2): 576-589 (2014) - [c10]Lipeng Wang, Fei Fei, Biao Jie, Daoqiang Zhang:
Combining Multiple Network Features for Mild Cognitive Impairment Classification. ICDM Workshops 2014: 996-1003 - [c9]Biao Jie, Dinggang Shen, Daoqiang Zhang:
Brain Connectivity Hyper-Network for MCI Classification. MICCAI (2) 2014: 724-732 - [c8]Biao Jie, Xi Jiang, Chen Zu, Daoqiang Zhang:
The New Graph Kernels on Connectivity Networks for Identification of MCI. MLINI@NIPS 2014: 12-20 - [c7]Chen Zu, Biao Jie, Songcan Chen, Daoqiang Zhang:
Label-Alignment-Based Multi-Task Feature Selection for Multimodal Classification of Brain Disease. MLINI@NIPS 2014: 51-59 - [c6]Fei Fei, Biao Jie, Lipeng Wang, Daoqiang Zhang:
Discriminative subnetwork mining for multiple thresholded connectivity-networks-based classification of mild cognitive impairment. PRNI 2014: 1-4 - 2013
- [c5]Biao Jie, Daoqiang Zhang, Heung-Il Suk, Chong-Yaw Wee, Dinggang Shen:
Integrating Multiple Network Properties for MCI Identification. MLMI 2013: 9-16 - [c4]Bo Cheng, Daoqiang Zhang, Biao Jie, Dinggang Shen:
Sparse Multimodal Manifold-Regularized Transfer Learning for MCI Conversion Prediction. MLMI 2013: 251-259 - [c3]Biao Jie, Daoqiang Zhang, Bo Cheng, Dinggang Shen:
Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer's Disease. MICCAI (1) 2013: 275-283 - [c2]Chong-Yaw Wee, Yang Li, Biao Jie, Zi-Wen Peng, Dinggang Shen:
Identification of MCI Using Optimal Sparse MAR Modeled Effective Connectivity Networks. MICCAI (2) 2013: 319-327 - 2012
- [c1]Biao Jie, Daoqiang Zhang, Chong-Yaw Wee, Dinggang Shen:
Structural Feature Selection for Connectivity Network-Based MCI Diagnosis. MBIA 2012: 175-184
Coauthor Index
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last updated on 2025-01-20 22:56 CET by the dblp team
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