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关键词

模式识别 7

目标识别 4

人脸识别 2

效果评估 2

特征抽取 2

语音识别 2

AR模型 1

CAD 1

CAM 1

CAPP 1

CCD影像 1

Laplacian特征映射 1

RBF神经网络 1

三维视觉知识；三维参数模型；心脏病理诊断；数据增强 1

中心聚类 1

主-客体化学 1

低维流形 1

信号消噪；深度自适应阈值学习网络；多尺度特征融合；调制识别 1

充电模式；充电时长；随机森林；长短期记忆网络（LSTM）；简化粒子群优化算法（SPSO） 1

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Multiobjective image recognition algorithm in the fully automatic die bonder

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

《机械工程前沿（英文）》 2006年第1卷第3期页码 313-316 doi: 10.1007/s11465-006-0026-y

摘要： It is a very important task to automatically fix the number of die in the image recognition system of a fully automatic die bonder. A multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposed in this paper. In the evolutionary process of GA, a clustering method is provided that utilizes information from the template and the fitness landscape of the current population. The whole population is grouped into different niches by the clustering method. Experimental results demonstrated that the number of target images could be determined by the algorithm automatically, and multiple targets could be recognized at a time. As a result, time consumed by one image recognition is shortened, the performance of the image recognition system is improved, and the atomization of the system is fulfilled.

关键词： clustering different recognition algorithm Algorithm multiobjective

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Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

《医学前沿（英文）》 2021年第15卷第4期页码 575-584 doi: 10.1007/s11684-020-0816-3

摘要： Spinal disease is an important cause of cervical discomfort, low back pain, radiating pain in the limbs, and neurogenic intermittent claudication, and its incidence is increasing annually. From the etiological viewpoint, these symptoms are directly caused by the compression of the spinal cord, nerve roots, and blood vessels and are most effectively treated with surgery. Spinal surgeries are primarily performed using two different techniques: spinal canal decompression and internal fixation. In the past, tactile sensation was the primary method used by surgeons to understand the state of the tissue within the operating area. However, this method has several disadvantages because of its subjectivity. Therefore, it has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognition, improve the accuracy of safe area location, and avoid surgical injury to tissues. Aside from traditional imaging methods, surgical sensing techniques based on force, bioelectrical impedance, and other methods have been gradually developed and tested in the clinical setting. This article reviews the progress of different tissue state recognition methods in spinal surgery and summarizes their advantages and disadvantages.

关键词： 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

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 917-920 doi: 10.1631/FITEE.1500080

摘要： Human action recognition is currently one of the most active research areas in computer vision. It has been widely used in many applications, such as intelligent surveillance, perceptual interface, and content-based video retrieval. However, some extrinsic factors are barriers for the development of action recognition; e.g., human actions may be observed from arbitrary camera viewpoints in realistic scene. Thus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchers have paid much attention to this issue. In this paper, we present a multi-view learning approach to recognize human actions from different views. As most existing multi-view learning algorithms often suffer from the problem of lacking data adaptiveness in the nearest neighborhood graph construction procedure, a robust locally adaptive multi-view learning algorithm based on learning multiple local L1-graphs is proposed. Moreover, an efficient iterative optimization method is proposed to solve the proposed objective function. Experiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU, demonstrate data adaptiveness, effectiveness, and efficiency of our algorithm. More importantly, when the feature dimension is correctly selected (i.e.,>60), the proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition accuracy on the three datasets.

关键词： 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

《环境科学与工程前沿（英文）》 2021年第15卷第6期 doi: 10.1007/s11783-021-1430-6

摘要：

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

关键词： 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

《信息与电子工程前沿（英文）》 2015年第16卷第12期页码 1046-1058 doi: 10.1631/FITEE.1500085

摘要： With the development of face recognition using sparse representation based classification (SRC), many relevant methods have been proposed and investigated. However, when the dictionary is large and the representation is sparse, only a small proportion of the elements contributes to the 1-minimization. Under this observation, several approaches have been developed to carry out an efficient element selection procedure before SRC. In this paper, we employ a metric learning approach which helps find the active elements correctly by taking into account the interclass/intraclass relationship and manifold structure of face images. After the metric has been learned, a neighborhood graph is constructed in the projected space. A fast marching algorithm is used to rapidly select the subset from the graph, and SRC is implemented for classification. Experimental results show that our method achieves promising performance and significant efficiency enhancement.

关键词： 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

《工程管理前沿（英文）》 2023年第10卷第2期页码 237-249 doi: 10.1007/s42524-021-0179-8

摘要： Named entity recognition (NER) is essential in many natural language processing (NLP) tasks such as information extraction and document classification. A construction document usually contains critical named entities, and an effective NER method can provide a solid foundation for downstream applications to improve construction management efficiency. This study presents a NER method for Chinese construction documents based on conditional random field (CRF), including a corpus design pipeline and a CRF model. The corpus design pipeline identifies typical NER tasks in construction management, enables word-based tokenization, and controls the annotation consistency with a newly designed annotating specification. The CRF model engineers nine transformation features and seven classes of state features, covering the impacts of word position, part-of-speech (POS), and word/character states within the context. The F1-measure on a labeled construction data set is 87.9%. Furthermore, as more domain knowledge features are infused, the marginal performance improvement of including POS information will decrease, leading to a promising research direction of POS customization to improve NLP performance with limited data.

关键词： NER NLP Chinese language construction document

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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

《化学科学与工程前沿（英文）》 2017年第11卷第2期页码 231-237 doi: 10.1007/s11705-017-1633-3

摘要： A novel gelator that contained both Schiff base and L-lysine moieties was synthesized and its gelation behavior was tested. This gelator can form gels in various organic solvents. The resulting gel can be applied as a fascinating platform for visual recognition of enantiomeric 1-(2-hydroxynaphthalen-1-yl)naphthalen-2-ol (BINOL) through selective gel collapse. In addition, the mechanism for the reaction of the gel with chiral BINOL was investigated by scanning electron microscope and H nuclear magnetic resonance.

关键词： gelator Schiff base chiral recognition gel formation gel collapse

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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

《信息与电子工程前沿（英文）》 2015年第16卷第4期页码 272-282 doi: 10.1631/FITEE.1400209

摘要： Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recent advances in artificial intelligence and pattern recognition. Most studies are based on 2D images, and their performance is usually computationally expensive. In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression features captured by Kinect sensors. To capture the deformation of the 3D mesh during facial expression, we combine the features of animation units (AUs) and feature point positions (FPPs) tracked by Kinect. A fusion algorithm based on improved emotional profiles (IEPs) and maximum confidence is proposed to recognize emotions with these real-time facial expression features. Experiments on both an emotion dataset and a real-time video show the superior performance of our method.

关键词： Kinect Emotion recognition Facial expression Real-time classification Fusion algorithm Support vector machine (SVM)

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

null

《医学前沿（英文）》 2013年第7卷第1期页码 126-131 doi: 10.1007/s11684-012-0236-0

摘要：

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.

关键词： 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

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 940-956 doi: 10.1631/FITEE.1500067

摘要： Named entity recognition (NER) is a core component in many natural language processing applications. Most NER systems rely on supervised machine learning methods, which depend on time-consuming and expensive annotations in different languages and domains. This paper presents a method for automatically building silver-standard NER corpora from Chinese Wikipedia. We refine novel and language-dependent features by exploiting the text and structure of Chinese Wikipedia. To reduce tagging errors caused by entity classification, we design four types of heuristic rules based on the characteristics of Chinese Wikipedia and train a supervised NE classifier, and a combined method is used to improve the precision and coverage. Then, we realize type identification of implicit mention by using boundary information of outgoing links. By selecting the sentences related with the domains of test data, we can train better NER models. In the experiments, large-scale NER corpora containing 2.3 million sentences are built from Chinese Wikipedia. The results show the effectiveness of automatically annotated corpora, and the trained NER models achieve the best performance when combining our silver-standard corpora with gold-standard corpora.

关键词： 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

《环境科学与工程前沿（英文）》 2019年第13卷第2期 doi: 10.1007/s11783-019-1102-y

摘要：

An image-recognition-based diagnosis system of pipe defect types was established.

1043 practical pipe images were gathered by CCTV robot in a southern Chinese city.

The overall accuracy of the system is 84% and the highest accuracy is 99.3%.

The accuracy shows positive correlation to the number of training samples.

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

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PD pattern recognition based on multi-fractal dimension in GIS

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

《机械工程前沿（英文）》 2008年第3卷第3期页码 270-275 doi: 10.1007/s11465-008-0042-1

摘要： 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.

关键词： substation high-speed discharge centrobaric network ultra-high frequency

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利用两类投影方法进行特征融合的人脸识别

张生亮,徐勇,杨健,杨静宇

《中国工程科学》 2006年第8卷第8期页码 50-55

摘要：

提出了利用两类投影抽取特征、用并行策略融合特征进行人脸识别的新方法。先用一维的基于向量的投影抽取一组特征，再用基于二维的图像投影的方法抽取一组特征，用复向量将样本的两组特征向量组合在一起，在复向量空间分析主分量(CPCA)，抽取人脸图像的鉴别特征。在FERET人脸库上的实验结果表明，该方法的识别性能比用单个特征有10%左右的提高。

关键词：特征融合线性鉴别分析(LDA) 特征抽取人脸识别

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基于径向基函数神经网络的滚动轴承故障模式的识别

陆爽,张子达,李萌

《中国工程科学》 2004年第6卷第2期页码 56-60

摘要：

径向基函数（RBF）神经网络是一种3层前馈性神经网络，它具有较强的函数逼近能力和分类能力。鉴于径向基函数神经网络的优点，在对滚动轴承振动信号特征分析的基础上，提出了采用时序方法对其建立AR模型，利用AR模型参数建立径向基函数神经网络，并用该网络对滚动轴承的故障模式进行了识别。理论和试验证明了该方法的有效性，且具有较高的识别精度。

关键词：滚动轴承振动信号 AR模型 RBF神经网络模式识别

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模式识别技术在泥浆浓度反演中的应用

李德军,吕艳华,王润田

《中国工程科学》 2007年第9卷第5期页码 81-84

摘要：

泥浆在建筑工程中使用非常普遍，合理地控制泥浆的物理性能对于建筑工程施工及其质量控制非常重要，通过声学方法可以有效地监测泥浆的体积浓度等物理参数。在通过声衰减和声速等介质的声学参数反演泥浆浓度的过程中，数据拟合的好坏直接影响到反演的精确程度。通过模式识别技术，利用聚类算法，对数据进行分类、归类处理，能有效的地提高反演的准确度。

关键词：模式识别最近邻法聚类算法泥浆浓度