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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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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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一适用于超多类手写汉字识别的新改型Adaboost算法

丁晓青,付强

《中国工程科学》 2009年第11卷第10期页码 19-24

摘要：

提出一种适用于超多类手写汉字识别的新改型Adaboost算法，采用基于描述性模型的多类分类器（modified quadratic discriminant function，MQDF）作为Adaboost基元分类器，可直接进行多类分类，无需将多类问题转化为多个两类问题处理，其训练复杂度大大低于已有的多类Adaboost算法。算法提出根据广义置信度更新样本权重，实验证明这种算法适用于大规模多类分类问题。为了降低算法的识别复杂度，提出从所有训练后得到的Adaboost基元分类器组中选择一个最优的基元分类器作为最终分类器的方法进行删减。在HCL2000及THOCR-HCD数据集上进行实验证明，所提改型Adaboost算法提高了识别率的有效性，该算法的相对错误率比现有最优算法分别下降了14.3 %，8.1 %和19.5 %。

关键词：多类Adaboost算法手写汉字识别广义置信度改进的二次鉴别函数

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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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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

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Research on constraint-based virtual assembly technologies

YANG Rundang, WU Dianliang, FAN Xiumin, YAN Juanqi

《机械工程前沿（英文）》 2007年第2卷第2期页码 243-249 doi: 10.1007/s11465-007-0043-5

摘要： To realize a constraint-based virtual assembly operation, the unified representations of the assembly constraint, the equivalent relation between the constraint and the degree of freedom (DOF), and the movement DOF reduction in a virtual environment are proposed. Several algorithms about the constraint treatment are submitted. First, the automatic recognition algorithm based on the assembly relation is used to determine the position and orientation relation between two geometry elements of constraint whether they meet the given errors. Second, to satisfy the new constraint, according to the positing solving algorithm, the position and orientation of an active part are modified with minimal adjustment after the part has satisfied the affirmed constraints. Finally, the algorithm of movement navigation based on the generalized coordinate system is put forward, and the part movement is guided. These algorithms have been applied to the integrated virtual assembly environment (IVAE) system. Experiments have indicated that these algorithms have well supported constraint treatments in the IVAE and realized the closer combination of the virtual and the real assembly processes.

关键词： movement DOF recognition algorithm assembly orientation combination

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基于语音识别的电磁调控智能超表面 Article

柏林, 刘元可, 徐亮, 张政, 王强, 蒋卫祥, 仇成伟, 崔铁军

《工程（英文）》 2023年第22卷第3期页码 185-190 doi: 10.1016/j.eng.2022.06.026

摘要：

本研究提出并实现了一种基于人类语音识别的智能超表面平台，用于对电磁波束进行可编程调控。该智能超表面平台由数字编码超表面、语音识别模块、单片机和数模转换器（DAC）电路组成，可根据预先存储的语音指令对电磁波进行智能控制。所构建的数字编码超表面包含6 × 6 个超级子单元，每个超级子单元由4 × 4 个嵌入了变容二极管的有源数字单元组成。语音识别模块配合DAC和单片机对语音指令进行识别，并生成对应的电压序列来控制超表面。此外，在超表面的设计过程中引入遗传算法，可有效优化超表面相位分布。为了验证智能超表面平台的性能，实验展示了雷达散射截面积缩减、涡旋波束生成和波束分裂三种典型功能。所提出的方案为调控电磁波提供了一种新途径，并在电磁和声学通信之间架起了一座桥梁。

关键词：语音识别可编程超表面遗传算法智能电磁调控

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过程神经网络的训练及其应用

何新贵,梁久祯,许少华

《中国工程科学》 2001年第3卷第4期页码 31-35

摘要：

研究过程神经网络的学习算法及其在过程模式识别中的应用。针对权值基展开的过程神经网络讨论了权值基的选取规则和对采样曲线的标准化处理问题，给出了含一个隐层的过程神经网络的误差反传播学习算法。以聚合化学反应和渗流实验两个具体实例验证了算法的有效性，也说明了过程神经网络的广泛应用前景。

关键词：过程神经网络学习算法模式识别化学反应渗流

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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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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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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