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Visual chiral recognition of 1,1′-binaphthol through enantioselective collapse of gel based on an amphiphilic

Xuhong Zhang, Haimiao Li, Xin Zhang, Meng An, Weiwei Fang, Haitao Yu

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 2,   Pages 231-237 doi: 10.1007/s11705-017-1633-3

Abstract: The resulting gel can be applied as a fascinating platform for visual recognition of enantiomeric 1-(In addition, the mechanism for the reaction of the gel with chiral BINOL was investigated by scanning

Keywords： gelator     Schiff base     chiral recognition     gel formation     gel collapse    

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Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 313-316 doi: 10.1007/s11465-006-0026-y

Abstract: It is a very important task to automatically fix the number of die in the image recognition system ofA multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposedAs a result, time consumed by one image recognition is shortened, the performance of the image recognition

Keywords： clustering     different     recognition algorithm     Algorithm     multiobjective    

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Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

Frontiers of Medicine 2021, Volume 15, Issue 4,   Pages 575-584 doi: 10.1007/s11684-020-0816-3

Abstract: has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognitionThis article reviews the progress of different tissue state recognition methods in spinal surgery and

Keywords： spinal surgery     tissue state recognition     image     force sensing     bioelectrical impedance    

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View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 917-920 doi: 10.1631/FITEE.1500080

Abstract: Human action recognition is currently one of the most active research areas in computer vision.However, some extrinsic factors are barriers for the development of action recognition; e.g., human actionsThus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchersExperiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU,proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition

Keywords： View-invariant     Action recognition     Multi-view learning     L1-norm     Local learning    

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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 6, doi: 10.1007/s11783-021-1430-6

Abstract:

• UV-vis absorption analyzer was applied in drainage type online recognition

Keywords： Drainage online recognition     UV-vis spectra     Derivative spectrum     Convolutional neural network    

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1046-1058 doi: 10.1631/FITEE.1500085

Abstract: With the development of face recognition using sparse representation based classification (SRC), many

Keywords： Face recognition     Sparse representation     Manifold structure     Metric learning     Subset selection    

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Named entity recognition for Chinese construction documents based on conditional random field

Frontiers of Engineering Management 2023, Volume 10, Issue 2,   Pages 237-249 doi: 10.1007/s42524-021-0179-8

Abstract: Named entity recognition (NER) is essential in many natural language processing (NLP) tasks such as information

Keywords： NER     NLP     Chinese language     construction document    

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UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 4,   Pages 272-282 doi: 10.1631/FITEE.1400209

Abstract: Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recentadvances in artificial intelligence and pattern recognition.In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression

Keywords： Kinect     Emotion recognition     Facial expression     Real-time classification     Fusion algorithm     Support vector    

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IDEEA activity monitor: validity of activity recognition for lying, reclining, sitting and standing

Yuyu Jiang, Janet L. Larson

Frontiers of Medicine 2013, Volume 7, Issue 1,   Pages 126-131 doi: 10.1007/s11684-012-0236-0

Abstract:

Recent evidence demonstrates the independent negative effects of sedentary behavior on health, but there are few objective measures of sedentary behavior. Most instruments measure physical activity and are not validated as measures of sedentary behavior. The purpose of this study was to evaluate the validity of the IDEEA system’s measures of sedentary and low-intensity physical activities: lying, reclining, sitting and standing. Thirty subjects, 14 men and 16 women, aged 23 to 77 years, body mass index (BMI) between 18 to 34 kg/m2, participated in the study. IDEEA measures were compared to direct observation for 27 activities: 10 lying in bed, 3 lying on a sofa, 1 reclining in a lawn chair, 10 sitting and 3 standing. Two measures are reported, the percentage of activities accurately identified and the percentage of monitored time that was accurately labeled by the IDEEA system for all subjects. A total of 91.6% of all observed activities were accurately identified and 92.4% of the total monitored time was accurately labeled. The IDEEA system did not accurately differentiate between lying and reclining so the two activities were combined for calculating accuracy. Using this approach the IDEEA system accurately identified 96% of sitting activities for a total of 97% of the monitored sitting time, 99% and 99% for standing, 87% and 88% for lying in bed, 87% and 88% for lying on the sofa, and 83% and 83% for reclining on a lawn chair. We conclude that the IDEEA system accurately recognizes sitting and standing positions, but it is less accurate in identifying lying and reclining positions. We recommend combining the lying and reclining activities to improve accuracy. The IDEEA system enables researchers to monitor lying, reclining, sitting and standing with a reasonable level of accuracy and has the potential to advance the science of sedentary behaviors and low-intensity physical activities.

Keywords： IDEEA     activity monitor     sedentary behavior    

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Automatically building large-scale named entity recognition corpora from Chinese Wikipedia

Jie ZHOU,Bi-cheng LI,Gang CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 940-956 doi: 10.1631/FITEE.1500067

Abstract: Named entity recognition (NER) is a core component in many natural language processing applications.

Keywords： NER corpora     Chinese Wikipedia     Entity classification     Domain adaptation     Corpus selection    

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Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

Frontiers of Environmental Science & Engineering 2019, Volume 13, Issue 2, doi: 10.1007/s11783-019-1102-y

Abstract:

An image-recognition-based diagnosis system of pipe defect types

Keywords： Sewer pipe defects     Defect diagnosing     Image recognition     Multi-features extraction     Support vector machine    

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Measurement and correlation of supercritical CO

Hiroshi MACHIDA, Ryosuke TAGUCHI, Yoshiyuki SATO, Louw J. FLOURUSSE, Cor J. PETERS, Richard L. SMITH

Frontiers of Chemical Science and Engineering 2009, Volume 3, Issue 1,   Pages 12-19 doi: 10.1007/s11705-009-0151-3

Abstract: industrial applications including: (1) general, (2) fuel desulfurization, (3) CO capture, and (4) chiral

Keywords： compact processes     chiral ionic liquids     separations     thermodynamic properties     equations of state    

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PD pattern recognition based on multi-fractal dimension in GIS

ZHANG Xiaoxing, YAO Yao, TANG Ju, ZHOU Qian, XU Zhongrong

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 3,   Pages 270-275 doi: 10.1007/s11465-008-0042-1

Abstract: This paper designs four types of gas insulated substation (GIS) defect models based on partial discharge (PD) characteristics and its defections. The GIS gray intensity images are constructed based on the mass specimens gathered by the ultra-high frequency and high-speed sampling systems. The multi-fractal dimension is founded on the box-counting dimension and multi-fractal theories. The GIS gray intensity images distillation methods, based on multi-fractal characteristics, is put forward. The box-counting dimension, multi-fractal dimension, and discharge centrobaric characteristics of the PD images are also extracted. The characteristic variables are then classified by the radial basis function (RBF) network. Identified results show that the methods can effectively elevate the discrimination of the four types of defects in GIS.

Keywords： substation     high-speed     discharge centrobaric     network     ultra-high frequency    

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Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks

Lu Shuang,Zhang Zida,Li Meng

Strategic Study of CAE 2004, Volume 6, Issue 2,   Pages 56-60

Abstract: Theory and experiment show that the recognition of fault pattern of rolling bearing based on radial basis

Keywords： rolling bearing     vibration signal     AR model     RBF neural networks     pattern recognition    

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A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Strategic Study of CAE 2006, Volume 8, Issue 8,   Pages 50-55

Abstract:

A novel face recognition algorithm based on two kinds of projection is presented in this paper.The experimental results indicate that the proposed method can achieve about 10% higher recognition accurate

Keywords： feature fusion     linear discriminant analysis (LDA)     feature extraction     face recognition    

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Title Author Date Type Operation

Visual chiral recognition of 1,1′-binaphthol through enantioselective collapse of gel based on an amphiphilic

Xuhong Zhang, Haimiao Li, Xin Zhang, Meng An, Weiwei Fang, Haitao Yu

Journal Article

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Journal Article

Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

Journal Article

View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

Journal Article

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Journal Article

Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Journal Article

Named entity recognition for Chinese construction documents based on conditional random field

Journal Article

UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

Journal Article

IDEEA activity monitor: validity of activity recognition for lying, reclining, sitting and standing

Yuyu Jiang, Janet L. Larson

Journal Article

Automatically building large-scale named entity recognition corpora from Chinese Wikipedia

Jie ZHOU,Bi-cheng LI,Gang CHEN

Journal Article

Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

Journal Article

Measurement and correlation of supercritical CO

Hiroshi MACHIDA, Ryosuke TAGUCHI, Yoshiyuki SATO, Louw J. FLOURUSSE, Cor J. PETERS, Richard L. SMITH

Journal Article

PD pattern recognition based on multi-fractal dimension in GIS

ZHANG Xiaoxing, YAO Yao, TANG Ju, ZHOU Qian, XU Zhongrong

Journal Article

Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks

Lu Shuang,Zhang Zida,Li Meng

Journal Article

A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Journal Article