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Representation learning via a semi-supervised stacked distance autoencoder for image classification Research Articles
Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7, Pages 963-1118 doi: 10.1631/FITEE.1900116
Keywords: 自动编码器;图像分类;半监督学习;神经网络
Deep 3D reconstruction: methods, data, and challenges Review Article
Caixia Liu, Dehui Kong, Shaofan Wang, Zhiyong Wang, Jinghua Li, Baocai Yin,lcxxib@emails.bjut.edu.cn,wangshaofan@bjut.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.2000068
Keywords: 深度学习模型;三维重建;循环神经网络;深度自编码器;生成对抗网络;卷积神经网络
NGAT: attention in breadth and depth exploration for semi-supervised graph representation learning Research Articles
Jianke HU, Yin ZHANG,yinzh@zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3, Pages 409-421 doi: 10.1631/FITEE.2000657
Keywords: Graph learning Semi-supervised learning Node classification Attention
Learning to select pseudo labels: a semi-supervised method for named entity recognition Research Articles
Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn
Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6, Pages 809-962 doi: 10.1631/FITEE.1800743
Keywords: 命名实体识别;无标注数据;深度学习;半监督学习方法
Two-level hierarchical feature learning for image classification Article
Guang-hui SONG,Xiao-gang JIN,Gen-lang CHEN,Yan NIE
Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 9, Pages 897-906 doi: 10.1631/FITEE.1500346
Keywords: Transfer learning Feature learning Deep convolutional neural network Hierarchical classification Spectral clustering
Neuro-heuristic computational intelligence for solving nonlinear pantograph systems Article
Muhammad Asif Zahoor RAJA, Iftikhar AHMAD, Imtiaz KHAN, Muhammed Ibrahem SYAM, Abdul Majid WAZWAZ
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4, Pages 464-484 doi: 10.1631/FITEE.1500393
Keywords: Neural networks Initial value problems (IVPs) Functional differential equations (FDEs) Unsupervised learning Genetic algorithms (GAs) Interior-point technique (IPT)
A Rough Fuzzy Neural Classifier
Zeng Huanglin,Wang Xiao
Strategic Study of CAE 2003, Volume 5, Issue 12, Pages 60-65
In this paper, the concepts of rough sets are used to define equivalence classes encoding input data sets, and eliminate redundant or insignificant attributes in data sets so that to reduce the complexity of system construction. In order to deal with ill-defined or real experimental data, an input object is represented as a fuzzy variable by fuzzy membership function, and the significant factor of the input feature corresponding to output pattern classification is incorporated to constitute a fuzzy inference so that to enhance nonlinear mapping classification. A new kind of rough fuzzy neural classifier and a learning algorithm with LSE are proposed in this paper. A integration of the merits of fuzzy and neural network technologies can not only accommodate overlapping classification and therefore increase the performance of nonlinear mapping classification, but ensure more efficiently to handle real life ambiguous and changing situations and to achieve tractability, robustness, and low-cost solutions.
Keywords: fuzzy sets rough sets neural networks pattern classification
Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving Research Articles
Yunpeng Wang, Kunxian Zheng, Daxin Tian, Xuting Duan, Jianshan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.1900637
Keywords: 自主驾驶;自动驾驶车辆;强化学习;监督学习
Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised fault classification Research Article
Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12, Pages 1814-1827 doi: 10.1631/FITEE.2200053
Keywords: Semi-supervised Active learning Ensemble learning Mixture discriminant analysis Fault classification
Interactive image segmentation with a regression based ensemble learning paradigm Article
Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7, Pages 1002-1020 doi: 10.1631/FITEE.1601401
Keywords: Interactive image segmentation Multivariate adaptive regression splines (MARS) Ensemble learning Thin-plate spline regression (TPSR) Semi-supervised learning Support vector regression (SVR)
Self-supervised graph learning with target-adaptive masking for session-based recommendation Research Article
Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1, Pages 73-87 doi: 10.1631/FITEE.2200137
Keywords: Session-based recommendation Self-supervised learning Graph neural networks Target-adaptive masking
Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images Research Article
Xiaolong CHEN, Xiaoqian MU, Jian GUAN, Ningbo LIU, Wei ZHOU,cxlcxl1209@163.com,guanjian_68@163.com
Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4, Pages 630-643 doi: 10.1631/FITEE.2000611
Keywords: Marine target detection Navigation radar Plane position indicator (PPI) images Convolutional neural network (CNN) Faster R-CNN (region convolutional neural network) method
Attention-based efficient robot grasp detection network Research Article
Xiaofei QIN, Wenkai HU, Chen XIAO, Changxiang HE, Songwen PEI, Xuedian ZHANG,xiaofei.qin@usst.edu.cn,obmmd_zxd@163.com
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 10, Pages 1430-1444 doi: 10.1631/FITEE.2200502
Keywords: Robot grasp detection Attention mechanism Encoder– decoder Neural network
Interactive medical image segmentation with self-adaptive confidence calibration
沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9, Pages 1332-1348 doi: 10.1631/FITEE.2200299
Keywords: Medical image segmentation Interactive segmentation Multi-agent reinforcement learning Confidence learning Semi-supervised learning
Estimating Rainfall Intensity Using an Image-Based Deep Learning Model Article
Hang Yin, Feifei Zheng, Huan-Feng Duan, Dragan Savic, Zoran Kapelan
Engineering 2023, Volume 21, Issue 2, Pages 162-174 doi: 10.1016/j.eng.2021.11.021
Urban flooding is a major issue worldwide, causing huge economic losses and serious threats to public safety. One promising way to mitigate its impacts is to develop a real-time flood risk management system; however, building such a system is often challenging due to the lack of high spatiotemporal rainfall data. While some approaches (i.e., ground rainfall stations or radar and satellite techniques) are available to measure and/or predict rainfall intensity, it is difficult to obtain accurate rainfall data with a desirable spatiotemporal resolution using these methods. This paper proposes an image-based deep learning model to estimate urban rainfall intensity with high spatial and temporal resolution. More specifically, a convolutional neural network (CNN) model called the image-based rainfall CNN (irCNN) model is developed using rainfall images collected from existing dense sensors (i.e., smart phones or transportation cameras) and their corresponding measured rainfall intensity values. The trained irCNN model is subsequently employed to efficiently estimate rainfall intensity based on the sensors' rainfall images. Synthetic rainfall data and real rainfall images are respectively utilized to explore the irCNN's accuracy in theoretically and practically simulating rainfall intensity. The results show that the irCNN model provides rainfall estimates with a mean absolute percentage error ranging between 13.5% and 21.9%, which exceeds the performance of other state-of-the-art modeling techniques in the literature. More importantly, the main feature of the proposed irCNN is its low cost in efficiently acquiring high spatiotemporal urban rainfall data. The irCNN model provides a promising alternative for estimating urban rainfall intensity, which can greatly facilitate the development of urban flood risk management in a real-time manner.
Keywords: Urban flooding Rainfall images Deep learning model Convolutional neural networks (CNNs) Rainfall intensity
Title Author Date Type Operation
Representation learning via a semi-supervised stacked distance autoencoder for image classification
Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn
Journal Article
Deep 3D reconstruction: methods, data, and challenges
Caixia Liu, Dehui Kong, Shaofan Wang, Zhiyong Wang, Jinghua Li, Baocai Yin,lcxxib@emails.bjut.edu.cn,wangshaofan@bjut.edu.cn
Journal Article
NGAT: attention in breadth and depth exploration for semi-supervised graph representation learning
Jianke HU, Yin ZHANG,yinzh@zju.edu.cn
Journal Article
Learning to select pseudo labels: a semi-supervised method for named entity recognition
Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn
Journal Article
Two-level hierarchical feature learning for image classification
Guang-hui SONG,Xiao-gang JIN,Gen-lang CHEN,Yan NIE
Journal Article
Neuro-heuristic computational intelligence for solving nonlinear pantograph systems
Muhammad Asif Zahoor RAJA, Iftikhar AHMAD, Imtiaz KHAN, Muhammed Ibrahem SYAM, Abdul Majid WAZWAZ
Journal Article
Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving
Yunpeng Wang, Kunxian Zheng, Daxin Tian, Xuting Duan, Jianshan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn
Journal Article
Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised fault classification
Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE
Journal Article
Interactive image segmentation with a regression based ensemble learning paradigm
Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU
Journal Article
Self-supervised graph learning with target-adaptive masking for session-based recommendation
Yitong WANG, Fei CAI, Zhiqiang PAN, Chengyu SONG,wangyitong20@nudt.edu.cn,caifei08@nudt.edu.cn,panzhiqiang@nudt.edu.cn,songchengyu@nudt.edu.cn
Journal Article
Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images
Xiaolong CHEN, Xiaoqian MU, Jian GUAN, Ningbo LIU, Wei ZHOU,cxlcxl1209@163.com,guanjian_68@163.com
Journal Article
Attention-based efficient robot grasp detection network
Xiaofei QIN, Wenkai HU, Chen XIAO, Changxiang HE, Songwen PEI, Xuedian ZHANG,xiaofei.qin@usst.edu.cn,obmmd_zxd@163.com
Journal Article
Interactive medical image segmentation with self-adaptive confidence calibration
沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰
Journal Article