资源类型

期刊论文 1600

会议视频 30

会议信息 3

年份

2024 1

2023 68

2022 133

2021 110

2020 89

2019 115

2018 91

2017 90

2016 70

2015 91

2014 82

2013 63

2012 81

2011 72

2010 72

2009 50

2008 73

2007 88

2006 39

2005 25

展开 ︾

关键词

风险分析 9

能源 7

分析 4

可持续发展 4

对策 4

影响因素 4

数值模拟 4

隧道 4

ANSYS 3

农业科学 3

抗击疫情 3

数值分析 3

环境 3

营养健康 3

裂缝 3

2035年 2

BNLAS 2

COVID-19 2

DX桩 2

展开 ︾

检索范围：

排序： 展示方式：

Assessment of fracture process in forta and polypropylene fiber-reinforced concrete using experimental analysisand digital image correlation

Seyed Hamid KALALI; Hamid ESKANDARI-NADDAF; Seyed Ali EMAMIAN

《结构与土木工程前沿（英文）》 2022年 第16卷 第12期   页码 1633-1652 doi: 10.1007/s11709-022-0876-3

摘要： This paper aims to characterize the evolution of the fracture process and the cracking behavior in Forta-Ferro (FF) and Polypropylene (PP) fiber-reinforced concrete under the uniaxial compressive loading using experimental analysis and digital image correlation (DIC) on the surface displacement. For this purpose, 6 mix designs, including two FF volume fractions of 0.10, and 0.20% and three PP volume fractions of 0.20, 0.30, and 0.40%, in addition to a control mix were evaluated according to compressive strength, modulus of elasticity, toughness index, and stress-strain curves. The influence of fibers on the microstructural texture of specimens was analyzed by scanning electron microscope (SEM) imaging. Results show that FF fiber-reinforced concrete specimens demonstrated increased ductility and strength compared to PP fiber. DIC results revealed that the major crack and fracture appeared at the peak load of the control specimen due to brittleness and sudden gain of large lateral strain, while a gradual increase in micro-crack quantity at 75% of peak load was observed in the fiber specimens, which thenbegan to connect with each other up to the final fracture. The accuracy of the results supports DIC as a reliable alternative for the characterization of the fracture process in fiber-reinforced concrete.

关键词： fiber-reinforced concrete     forta-ferro and polypropylene fiber     fracture process     cracking behavior     digital image correlation    

HTML PDF 收藏

15th International Congress for Stereology and Image Analysis 第十五届国际体视学与图像分析学术会议

会议日期： 2019年05月27日

会议地点： 丹麦/奥胡斯

主办单位： 国际体视学与图像分析学会(ISSIA)

Deep learning in digital pathology image analysis: a survey

Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu

《医学前沿（英文）》 2020年 第14卷 第4期   页码 470-487 doi: 10.1007/s11684-020-0782-9

摘要： deep learning (DL) has achieved state-of-the-art performance in many digital pathology analysis tasks. Traditional methods usually require hand-crafted domain-specific features, and DL methods can learn representations without manually designed features. In terms of feature extraction, DL approaches are less labor intensive compared with conventional machine learning methods. In this paper, we comprehensively summarize recent DL-based image analysis studies in histopathology, including different tasks (e.g., classification, semantic segmentation, detection, and instance segmentation) and various applications (e.g., stain normalization, cell/gland/region structure analysis). DL methods can provide consistent and accurate outcomes. DL is a promising tool to assist pathologists in clinical diagnosis.

关键词： pathology     deep learning     segmentation     detection     classification    

HTML PDF 收藏

Image analysis of soil failure on defective underground pipe due to cyclic water supply and drainage

Toshifumi MUKUNOKI, Naoko KUMANO, Jun OTANI

《结构与土木工程前沿（英文）》 2012年 第6卷 第2期   页码 85-100 doi: 10.1007/s11709-012-0159-5

摘要： The ground subsidence on the underground pipe often is caused with the reduction of the effective stress and the loss of suction in the base course and then, soil drainage into the pipe. The final formation of the cavity growth in the ground was observed as the ground subsidence. Authors focused this problem and hence performed model tests with water-inflow and drainage cycle in the model ground. The mechanism of cavity generation in the model ground was observed using an X-ray Computed Tomography (CT) scanner. In those studies, water was supplied into the model grounds from the defected underground pipe model in case of the change of relative density and grain size distribution. As results, it was observed that the loosening area was generated from the defected part with water-inflow and some of the soil particles in the ground were drained into the underground pipe through the defected part. And afterward, the cavity was generated just above the defected part of the model pipe in the ground. Based on this observation, it might be said that the bulk density of soil around the defected pipe played one of key factor to generate the cavity in the ground. Moreover, the dimension of the defected part should be related to the magnification of the ground subsidence, in particular, crack width on a sewerage pipe and particle size would be the quantitative factor to evaluate the magnification of the ground subsidence. ?In this paper, it was concluded that the low relative density of soil would become the critical factor to cause the fatal failure of model ground if the maximum grain size was close to the dimension of crack width of defective part. The fatal collapse of the ground with high relative density more than 80% would be avoided in a few cycles of water inflow and soil drainage.

关键词： relative density     grain property     model test     road subsidence     underground pipe     image processing     X-ray CT    

HTML PDF 收藏

Turbidity-adaptive underwater image enhancement method using image fusion

《机械工程前沿（英文）》 2022年 第17卷 第3期 doi: 10.1007/s11465-021-0669-8

摘要： Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.

关键词： turbidity     underwater image enhancement     image fusion     underwater robots     visibility    

HTML PDF 收藏

Detection of Huanglongbing (citrus greening) based on hyperspectral image analysis and PCR

Kejian WANG, Dongmei GUO, Yao ZHANG, Lie DENG, Rangjin XIE, Qiang LV, Shilai YI, Yongqiang ZHENG, Yanyan MA, Shaolan HE

《农业科学与工程前沿（英文）》 2019年 第6卷 第2期   页码 172-180 doi: 10.15302/J-FASE-2019256

摘要：

Huanglongbing (HLB, citrus greening) is one of the most serious quarantine diseases of citrus worldwide. To monitor in real-time, recognize diseased trees, and efficiently prevent and control HLB disease in citrus, it is necessary to develop a rapid diagnostic method to detect HLB infected plants without symptoms. This study used Newhall navel orange plants as the research subject, and collected normal color leaf samples and chlorotic leaf samples from a healthy orchard and an HLB-infected orchard, respectively. First, hyperspectral data of the upper and lower leaf surfaces were obtained, and then the polymerase chain reaction (PCR) was used to detect the HLB bacterium in each leaf. The PCR test results showed that all samples from the healthy orchard were negative, and a portion of the samples from the infected orchard were positive. According to these results, the leaf samples from the orchards were divided into disease-free leaves and HLB-positive leaves, and the least squares support vector machine recognition model was established based on the leaf hyperspectral reflectance. The effect on the model of the spectra obtained from the upper and lower leaf surfaces was investigated and different pretreatment methods were compared and analyzed. It was observed that the HLB recognition rate values of the calibration and validation sets based on upper leaf surface spectra under 9-point smoothing pretreatment were 100% and 92.5%, respectively. The recognition rate values based on lower leaf surface spectra under the second-order derivative pretreatment were also 100% and 92.5%, respectively. Both upper and lower leaf surface spectra were available for recognition of HLB-infected leaves, and the HLB PCR-positive leaves could be distinguished from the healthy by the hyperspectral modeling analysis. The results of this study show that early and nondestructive detection of HLB-infected leaves without symptoms is possible, which provides a basis for the hyperspectral diagnosis of citrus with HLB.

关键词： citrus     HLB     hyperspectral     identification     PCR    

HTML PDF 收藏

Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

《信息与电子工程前沿（英文）》 2015年 第16卷 第3期   页码 227-237 doi: 10.1631/FITEE.1400217

摘要： We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE) sampling for compressive sensing imaging. First, source images are compressed by compressive sensing, to facilitate the transmission of the sensor. In the fusion phase, the image gradient is calculated to reflect the abundance of its contour information. By compositing the gradient of each image, gradient-based weights are obtained, with which compressive sensing coefficients are achieved. Finally, inverse transformation is applied to the coefficients derived from fusion, and the fused image is obtained. Information entropy (IE), Xydeas’s and Piella’s metrics are applied as non-reference objective metrics to evaluate the fusion quality in line with different fusion schemes. In addition, different image fusion application scenarios are applied to explore the scenario adaptability of the proposed scheme. Simulation results demonstrate that the gradient-based scheme has the best performance, in terms of both subjective judgment and objective metrics. Furthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion scenarios.

关键词： Compressive sensing (CS)     Image fusion     Gradient-based image fusion     CS-based image fusion    

HTML PDF 收藏

Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

《机械工程前沿（英文）》 2009年 第4卷 第1期   页码 77-82 doi: 10.1007/s11465-009-0013-1

摘要： An edge detection method for the measurement of steel plate’s thermal expansion is proposed in this paper, where the shrinkage of a steel plate is measured when temperature drops. First, images are picked up by an imaging system; a method of regional edge detection based on grayscales’ sudden change is then applied to detect the edges of the steel plate; finally, pixel coordinates of the edge position are transformed to physical coordinates through calibration parameters. The experiment shows that the real-time, high precision, and non-contact measurement of the steel plate’s edge position under high temperature can be realized using the imaging measurement method established in this paper.

关键词： thermal expansion     image measurement     edge detection     image calibration    

HTML PDF 收藏

一种快速均匀的采用尺度不变特征变换描述符进行基于内容的卫星图像配准方法 Article

Hamed BOZORGI, Ali JAFARI

《信息与电子工程前沿（英文）》 2017年 第18卷 第8期   页码 1108-1116 doi: 10.1631/FITEE.1500295

摘要： 另外，SIFT算法提取的本地特征具有较高维度，导致计算过程耗时过长以及对保存相关信息的储存空间要求过高，而这两点也是在基于内容图像检索（content-based image retrieval, CBIR将参考数据库中每副图像的本地特征单独分为一类后，采用线性判别分析（linear discriminant analysis, LDA）方法将本地SIFT特征转变为全局特征，同时不为降低特征空间的维度。

关键词： 基于内容的卫星图像配准；特征点分布；图像配准；线性判别准则；遥感；尺度不变特征变换    

HTML PDF 收藏

利用机器视觉技术对化工厂管道进行自动视觉泄漏检测与定位 Reiew

Mina Fahimipirehgalin, Emanuel Trunzer, Matthias Odenweller, Birgit Vogel-Heuser

《工程（英文）》 2021年 第7卷 第6期   页码 758-776 doi: 10.1016/j.eng.2020.08.026

摘要：

在大型化工厂中，输送液体的管道的泄漏是一个重要的问题。管道的破损不仅会影响工厂的正常运行，同时也增加了维护成本。此外，还会使操作人员的生命安全受到威胁。因此，管道泄漏的检测与定位是维护和状态监测中的关键任务。近年来，大型工厂利用红外（IR）相机进行泄漏检测。红外相机可捕捉温度比周围环境温度高（或低）的液体泄漏。本文针对化工厂中的管道泄漏，提出了一种基于红外视频数据和机器视觉技术的检测与定位方法。由于所提出的方法是以视觉技术为基础，无需考虑泄漏液体的物理性质，因此其适用于任何类型的液体（水、油等）泄漏检测。在本方法中，首先对后续帧进行减影和分块处理，然后对每一分块进行主成分分析，提取特征；接着将分块内所有减影帧都转换为特征向量（作为块分类的依据），根据特征向量，采用k-最近邻算法将块分为正常（无泄漏）和异常（泄漏）两类；最后在各异常块上确定泄漏的位置。本文使用了两种不同格式的数据集（由红外相机拍摄的实验室工厂演示装置的视频图像组成）对上述方法进行评估。结果表明，本文提出的利用红外视频进行管道泄漏检测与定位的方法前景可观，具有较高的检测精度以及合理的检测时间。本文最后讨论了该方法在工厂进行实际推广的可能性及局限性。

关键词： 泄漏检测与定位     图像分析     图像预处理     主成分分析     k-最近邻分类    

HTML PDF 收藏

Image-based fall detection and classification of a user with a walking support system

Sajjad TAGHVAEI, Kazuhiro KOSUGE

《机械工程前沿（英文）》 2018年 第13卷 第3期   页码 427-441 doi: 10.1007/s11465-017-0465-7

摘要：

The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems. We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user’s depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called “RT Walker”) by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user’s motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.

关键词： fall detection     walking support     hidden Markov model     multivariate analysis    

HTML PDF 收藏

Quantification of coarse aggregate shape in concrete

Xianglin GU,Yvonne TRAN,Li HONG

《结构与土木工程前沿（英文）》 2014年 第8卷 第3期   页码 308-321 doi: 10.1007/s11709-014-0266-6

摘要： The objective of this study is to choose indices for the characterization of aggregate form and angularity for large scale application. For this purpose, several parameters for aggregate form and angularity featured in previous research are presented. Then, based on these established parameters, 200 coarse quartzite aggregates are analyzed herein by using image processing technology. This paper also analyzes the statistical distributions of parameters for aggregate form and angularity as well as the correlation between form and angularity parameters. It was determined that the parameters for form or angularity of coarse aggregates could be fitted by either normal distribution or log-normal distribution at a 95% confidence level. Some of the form parameters were influenced by changes in angularity characteristics, while aspect ratio and angularity using outline slope, area ratio and radius angularity index, and aspect ratio and angularity index were independent of each other, respectively; and consequently, the independent parameters could be used to quantify the aggregate form and angularity for the purpose to study the influence of aggregate shape on the mechanical behavior of concrete. Furthermore, results from this study’s in-depth investigations showed that the aspect ratio and the angularity index can further understanding of the effects of coarse aggregates form and angularity on concrete mechanical properties, respectively. Finally, coarse aggregates with the same content, type and surfaces texture, but different aspect ratios and angularity indices were used to study the influence of coarse aggregate form and angularity on the behavior of concrete. It was revealed that the splitting tensile strength of concrete increased with increases in the aspect ratio or angularity index of coarse aggregates.

关键词： coarse aggregate     form     angularity     digital image analysis     statistical distribution     splitting tensile strength    

HTML PDF 收藏

Deformable image registration with geometric changes

Yu LIU,Bo ZHU

《信息与电子工程前沿（英文）》 2015年 第16卷 第10期   页码 829-837 doi: 10.1631/FITEE.1500045

摘要： Geometric changes present a number of difficulties in deformable image registration. In this paper, we propose aglobal deformation framework to model geometric changes whilst promoting a smooth transformation between source and target images. To achieve this, we have developed an innovative model which significantly reduces the side effects of geometric changes in image registration, and thus improves the registration accuracy. Our key contribution is the introduction of a sparsity-inducing norm, which is typically L1 norm regularization targeting regions where geometric changes occur. This preserves the smoothness of global transformation by eliminating local transformation under different conditions. Numerical solutions are discussed and analyzed to guarantee the stability and fast convergence of our algorithm. To demonstrate the effectiveness and utility of this method, we evaluate it on both synthetic data and real data from traumatic brain injury (TBI). We show that the transformation estimated from our model is able to reconstruct the target image with lower instances of error than a standard elastic registration model.

关键词： Geometric changes     Image registration     Sparsity     Traumatic brain injury (TBI)    

HTML PDF 收藏

A building unit decomposition model for energy leakage by infrared thermography image analysis

Yan SU, Fangjun HONG, Lianjie SHU

《能源前沿（英文）》 2020年 第14卷 第4期   页码 901-921 doi: 10.1007/s11708-020-0679-y

摘要： A quantitative energy leakage model was developed based on the thermography image data measured for both external and internal building surfaces. The infrared thermography images of both surfaces of doors, windows, and walls of an office building in the Hengqin Campus of University of Macao were taken at various times in a day for four seasons. The transient heat flux for sample units were obtained based on measurements of the seasonal transient local temperature differences and calculations of the effective thermal conductivity from the multiple-layer porous medium conduction model. Effects of construction unit types, orientations, and seasons were quantitatively investigated with unit transient orientation index factors. The corresponding electric energy consumption was calculated based on the air conditioning system coefficient of performance of heat pump and refrigerator cycles for different seasons. The model was validated by comparing to the electric meter records of energy consumption of the air conditioning system. The uncertainties of the predicted total building energy leakage are about 14.7%, 12.8%, 12.4%, and 15.8% for the four seasons, respectively. The differences between the predicted electric consumption and meter values are less than 13.4% and 5.4% for summer and winter, respectively. The typical daily thermal energy leakage value in winter is the highest among the four seasons. However, the daily electric energy consumption by the air conditioning system in summer and autumn is higher than that in winter. The present decomposition model for energy leakage is expected to provide a practical tool for quantitative analysis of energy leakage of buildings.

关键词： heat conductivity     heat coefficient     heat &fllig     ux     infrared thermography     thermal image    

HTML PDF 收藏

Digital image correlation-based structural state detection through deep learning

《结构与土木工程前沿（英文）》 2022年 第16卷 第1期   页码 45-56 doi: 10.1007/s11709-021-0777-x

摘要： This paper presents a new approach for automatical classification of structural state through deep learning. In this work, a Convolutional Neural Network (CNN) was designed to fuse both the feature extraction and classification blocks into an intelligent and compact learning system and detect the structural state of a steel frame; the input was a series of vibration signals, and the output was a structural state. The digital image correlation (DIC) technology was utilized to collect vibration information of an actual steel frame, and subsequently, the raw signals, without further pre-processing, were directly utilized as the CNN samples. The results show that CNN can achieve 99% classification accuracy for the research model. Besides, compared with the backpropagation neural network (BPNN), the CNN had an accuracy similar to that of the BPNN, but it only consumes 19% of the training time. The outputs of the convolution and pooling layers were visually displayed and discussed as well. It is demonstrated that: 1) the CNN can extract the structural state information from the vibration signals and classify them; 2) the detection and computational performance of the CNN for the incomplete data are better than that of the BPNN; 3) the CNN has better anti-noise ability.

关键词： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

HTML PDF 收藏

标题 作者 时间 类型 操作

Assessment of fracture process in forta and polypropylene fiber-reinforced concrete using experimental analysisand digital image correlation

Seyed Hamid KALALI; Hamid ESKANDARI-NADDAF; Seyed Ali EMAMIAN

期刊论文

15th International Congress for Stereology and Image Analysis 第十五届国际体视学与图像分析学术会议

2019年05月27日

会议信息

Deep learning in digital pathology image analysis: a survey

Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu

期刊论文

Image analysis of soil failure on defective underground pipe due to cyclic water supply and drainage

Toshifumi MUKUNOKI, Naoko KUMANO, Jun OTANI

期刊论文

Turbidity-adaptive underwater image enhancement method using image fusion

期刊论文

Detection of Huanglongbing (citrus greening) based on hyperspectral image analysis and PCR

Kejian WANG, Dongmei GUO, Yao ZHANG, Lie DENG, Rangjin XIE, Qiang LV, Shilai YI, Yongqiang ZHENG, Yanyan MA, Shaolan HE

期刊论文

Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

期刊论文

Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

期刊论文

一种快速均匀的采用尺度不变特征变换描述符进行基于内容的卫星图像配准方法

Hamed BOZORGI, Ali JAFARI

期刊论文

利用机器视觉技术对化工厂管道进行自动视觉泄漏检测与定位

Mina Fahimipirehgalin, Emanuel Trunzer, Matthias Odenweller, Birgit Vogel-Heuser

期刊论文

Image-based fall detection and classification of a user with a walking support system

Sajjad TAGHVAEI, Kazuhiro KOSUGE

期刊论文

Quantification of coarse aggregate shape in concrete

Xianglin GU,Yvonne TRAN,Li HONG

期刊论文

Deformable image registration with geometric changes

Yu LIU,Bo ZHU

期刊论文

A building unit decomposition model for energy leakage by infrared thermography image analysis

Yan SU, Fangjun HONG, Lianjie SHU

期刊论文

Digital image correlation-based structural state detection through deep learning

期刊论文