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学者姓名：庞俊彪
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Abstract ：
本发明涉及一种面向食品安全的多模态人机交互方法和系统、电子设备及存储介质。该方法包括：获取用于生成多模态食品安全知识图谱的相关多模态数据源；针对所述多模态数据源，利用文档处理方法、图像识别工具以及知识抽取工具抽取多模态数据的信息，获得多模态食品安全知识；基于所述食品安全知识，生成所述多模态食品安全知识图谱；以及构建多模态人机交互系统，并基于所述多模态食品安全知识图谱实现对多模态数据的人机交互。本发明将现有的多模态食品安全数据整理并生成食品安全知识图谱，实现针对多模态数据的人机交互，能够更好的展示食品安全信息，从而替代食品安全领域专家的知识，实现食品安全领域的智能化。
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| GB/T 7714 | 吕龙龙 , 张永恒 , 庞俊彪 et al. 面向食品安全的多模态人机交互方法和系统、设备及介质 : CN202110969283.0[P]. | 2021-08-23 . |
| MLA | 吕龙龙 et al. "面向食品安全的多模态人机交互方法和系统、设备及介质" : CN202110969283.0. | 2021-08-23 . |
| APA | 吕龙龙 , 张永恒 , 庞俊彪 , 黄庆明 , 尹宝才 . 面向食品安全的多模态人机交互方法和系统、设备及介质 : CN202110969283.0. | 2021-08-23 . |
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Abstract ：
近年来,随着公共交通领域大数据、云计算、移动支付等新兴科技的应用,城市公交、轨道交通等公共交通行业都推出了二维码App实现了"刷手机"乘车.在为用户出行带来便捷的同时,出现了各App平台的信息数据不互联互通和二维码规范不一等问题.这给用户换乘交通工具时带来了不便,同时增加了交通部门的管理成本.本文基于HTTPS(Hyper Text Transfer Protocol over Secure Socket Layer)通信协议、HTML5(HyperText Markup Language 5)通信协议以及MQ(Message Queue)通信协议等多种通信协议构建一码通乘平台,统一各平台的二维码规范和对信息数据,让公共交通资源和数据管理朝着高效化、便捷化、规范化的方向发展.
Keyword ：
Message Queue通信协议 Message Queue通信协议 HTML 5通信协议 HTML 5通信协议 跨平台 跨平台 HTTPS通信协议 HTTPS通信协议
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| GB/T 7714 | 隋莉颖 , 于海涛 , 杜勇 et al. 基于多通信协议的一码通乘平台技术研究 [J]. | 电脑知识与技术 , 2021 , 17 (27) : 10-12 . |
| MLA | 隋莉颖 et al. "基于多通信协议的一码通乘平台技术研究" . | 电脑知识与技术 17 . 27 (2021) : 10-12 . |
| APA | 隋莉颖 , 于海涛 , 杜勇 , 边嘉乐 , 庞俊彪 . 基于多通信协议的一码通乘平台技术研究 . | 电脑知识与技术 , 2021 , 17 (27) , 10-12 . |
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Abstract ：
随着互联网移动支付技术的蓬勃发展,轨道交通、城市公交及远郊公交等交通行业均构建了自己的移动付费乘车平台.但前期多种交通出行运营方付费二维码不通用、数据信息不互通,给交通数据管理、信息反馈和用户出行带来了诸多不便.因此,市民对交通出行付费方式统一化的呼声越来越高.文中基于中心接入规范的交通一码通乘应用方案,提出中心统一发码平台、中心公共管理平台和中心数据交换平台,解决二维码规范不同、用户信息管理不统一、业务规则及管理机制不一致等问题.一码通乘平台的构建可方便市民出行付费,便于交通运营企业的管理,同时为未来城市规划提供更充实的数据支撑.
Keyword ：
城市交通 城市交通 公共交通 公共交通 中心接入规范 中心接入规范 一码通乘 一码通乘
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| GB/T 7714 | 隋莉颖 , 于海涛 , 杜勇 et al. 基于中心接入规范的交通一码通乘 [J]. | 交通科技 , 2021 , (5) : 95-99 . |
| MLA | 隋莉颖 et al. "基于中心接入规范的交通一码通乘" . | 交通科技 5 (2021) : 95-99 . |
| APA | 隋莉颖 , 于海涛 , 杜勇 , 边嘉乐 , 庞俊彪 . 基于中心接入规范的交通一码通乘 . | 交通科技 , 2021 , (5) , 95-99 . |
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Abstract ：
Pavement crack detection is of great significance for road maintenance. However, the complexity of road surfaces and the irregularity of cracks make it difficult to accurately detect crack regions. We propose a crack detection method based on structural features for the patch-wise crack detection. The novelty of this method lies on the fusion of the local patches in a multi-staged strategy. Deep supervision learning is further used to learn these features at each stage. The fusion features model the structural relevance among cracks. The experimental results prove the effectiveness of our method on the dataset collected from the industrial environments. Among these state-of-the-art methods we compared, our model achieved the best experimental results with an AP 86.97%.
Keyword ：
structural feature extraction structural feature extraction deep supervision deep supervision crack detection crack detection
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| GB/T 7714 | Duan, Lijuan , Zeng, Jun , Pang, Junbiao et al. Pavement Crack Detection Using Multi-stage Structural Feature Extraction Model [J]. | 2021 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) , 2021 : 969-973 . |
| MLA | Duan, Lijuan et al. "Pavement Crack Detection Using Multi-stage Structural Feature Extraction Model" . | 2021 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (2021) : 969-973 . |
| APA | Duan, Lijuan , Zeng, Jun , Pang, Junbiao , Wang, Junzhe . Pavement Crack Detection Using Multi-stage Structural Feature Extraction Model . | 2021 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) , 2021 , 969-973 . |
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Abstract ：
本发明提供一种城市交通动态知识图谱的构建方法及装置，方法包括：根据城市交通站点的地点节点以及地点节点属性特征，确定地点节点关系模型；根据预设采样周期获取的地点节点、地点节点属性特征以及地点节点关系模型，构建城市交通动态知识图谱；其中，地点节点属性特征包括：地点节点兴趣点属性特征、地点节点社会事件属性特征、地点节点路链交通属性特征以及地点节点交通属性特征。所述装置用于执行上述方法。本发明提供的城市交通动态知识图谱的构建方法及装置，通过构建城市交通动态知识图谱，能够提高知识图谱的动态特征，更准确的对交通变化进行预测，提高城市交通服务。
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| GB/T 7714 | 庞俊彪 , 王哲焜 , 吕龙龙 et al. 城市交通动态知识图谱的构建方法及装置 : CN202011364436.0[P]. | 2020-11-27 . |
| MLA | 庞俊彪 et al. "城市交通动态知识图谱的构建方法及装置" : CN202011364436.0. | 2020-11-27 . |
| APA | 庞俊彪 , 王哲焜 , 吕龙龙 , 黄庆明 , 尹宝才 . 城市交通动态知识图谱的构建方法及装置 : CN202011364436.0. | 2020-11-27 . |
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Abstract ：
本发明实施例提供一种路面裂缝检测方法、装置、电子设备及介质；该方法包括采集道路的路面图像；对所述路面图像进行预处理，得到分辨率梯度变化的多个输入图像；将所述多个输入图像输入预先训练的路面裂缝检测模型，得到计算结果；其中，所述路面裂缝检测模型是基于样本路面图像和所述样本路面图像的裂缝标记数据训练得到的，所述路面裂缝检测模型包括多个阶段，每个阶段间进行多次多尺度融合；根据所述路面裂缝检测模型的计算结果，输出检测结果。本发明实施例通过输入分辨率梯度变化的多个输入图像，使用具有多尺度融合结构的路面裂缝检测模型，实现了对复杂情况下的路面裂缝检测，减弱了噪声影响，提高了检测精度。
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| GB/T 7714 | 曾君 , 庞俊彪 , 李培育 et al. 路面裂缝检测方法、装置、电子设备及存储介质 : CN202011454642.0[P]. | 2020-12-10 . |
| MLA | 曾君 et al. "路面裂缝检测方法、装置、电子设备及存储介质" : CN202011454642.0. | 2020-12-10 . |
| APA | 曾君 , 庞俊彪 , 李培育 , 段立娟 , 黄庆明 . 路面裂缝检测方法、装置、电子设备及存储介质 : CN202011454642.0. | 2020-12-10 . |
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Abstract ：
Automatic crack detection from pavement images is an import research field. Meanwhile, crack detection is a challenge task: (1) manual labels are subjective because of low contrast between crack and the surrounding pavement and heavy workload; (2) the excessive dependence of supervised deep learning training on labels. To address these problems, we present an unsupervised method for learning mapping to translate crack images to binary images based on generative adversarial network. We introduce the cyclic consistent loss to increase accuracy of crack localization. Eight residual blocks connected convolutional neural network for feature extraction is used as generator and a 5-layer fully convolutional network is used as discriminator. We analyze the proposed framework and provide qualitative and quantitative comparison. The experimental results show that the proposed method achieves a better performance than several existing methods. © 2020 ACM.
Keyword ：
Binary images Binary images Crack detection Crack detection Convolutional neural networks Convolutional neural networks Convolution Convolution Multimedia signal processing Multimedia signal processing Deep learning Deep learning Pavements Pavements Multimedia systems Multimedia systems
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| GB/T 7714 | Duan, Lijuan , Geng, Huiling , Pang, Junbiao et al. Unsupervised Pixel-level Crack Detection Based on Generative Adversarial Network [C] . 2020 : 6-10 . |
| MLA | Duan, Lijuan et al. "Unsupervised Pixel-level Crack Detection Based on Generative Adversarial Network" . (2020) : 6-10 . |
| APA | Duan, Lijuan , Geng, Huiling , Pang, Junbiao , Zeng, Jun . Unsupervised Pixel-level Crack Detection Based on Generative Adversarial Network . (2020) : 6-10 . |
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Abstract ：
Organizing webpages into interesting topics is one of the key steps to understand the trends from multimodal Web data. The sparse, noisy, and less-constrained user-generated content results in inefficient feature representations. These descriptors unavoidably cause that a detected topic still contains a certain number of the false detected webpages, which further make a topic be less coherent, less interpretable, and less useful. In this paper, we address this problem from a viewpoint interpreting a topic by its prototypes, and present a two-step approach to achieve this goal. Following the detection-by-ranking approach, a sparse Poisson deconvolution is proposed to learn the intratopic similarities between webpages. To find the prototypes, leveraging the intratopic similarities, top-k diverse yet representative prototype webpages are identified from a submodularity function. Experimental results not only show the improved accuracies for the Web topic detection task, but also increase the interpretation of a topic by its prototypes on two public datasets.
Keyword ：
Poisson deconvolution Poisson deconvolution sparsity sparsity Web topic detection Web topic detection submodularity submodularity prototype learning (PL) prototype learning (PL) topic interpretation topic interpretation
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| GB/T 7714 | Pang, Junbiao , Hu, Anjing , Huang, Qingming et al. Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution [J]. | IEEE TRANSACTIONS ON CYBERNETICS , 2019 , 49 (3) : 1072-1083 . |
| MLA | Pang, Junbiao et al. "Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution" . | IEEE TRANSACTIONS ON CYBERNETICS 49 . 3 (2019) : 1072-1083 . |
| APA | Pang, Junbiao , Hu, Anjing , Huang, Qingming , Tian, Qi , Yin, Baocai . Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution . | IEEE TRANSACTIONS ON CYBERNETICS , 2019 , 49 (3) , 1072-1083 . |
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Abstract ：
本发明实施例提供一种裂缝宽度测量方法及装置，所述方法包括：获取摄像头采集到的裂缝图像，并根据所述摄像头到裂缝表面的距离，以及所述摄像头拍摄所述裂缝图像时的焦距和像素，计算所述裂缝图像上单个像素点的宽度；识别所述裂缝图像的裂缝像素点，在所述裂缝像素点中选择单个裂缝像素点作为测量像素点，以所述测量像素点为中心点，在所述裂缝图像中获取裂缝块；根据预设算法计算得到所述裂缝块的裂缝主轴，获取经过所述测量像素点且垂直于所述裂缝主轴的直线；统计所述直线上的裂缝像素点的个数，通过所述裂缝像素点的个数及所述单个像素点的宽度计算得到裂缝宽度。采用本方法能够得到更高准确率的裂缝宽度计算结果。
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| GB/T 7714 | 庞俊彪 , 耿慧玲 , 段立娟 et al. 裂缝宽度测量方法及装置 : CN201911182766.5[P]. | 2019-11-27 . |
| MLA | 庞俊彪 et al. "裂缝宽度测量方法及装置" : CN201911182766.5. | 2019-11-27 . |
| APA | 庞俊彪 , 耿慧玲 , 段立娟 , 曾君 , 黄庆明 . 裂缝宽度测量方法及装置 : CN201911182766.5. | 2019-11-27 . |
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Abstract ：
Crack width is an important indicator to diagnose the safety of constructions, e.g., asphalt road, concrete bridge. In practice, measuring crack width is a challenge task: (1) the irregular and non-smooth boundary makes the traditional method inefficient; (2) pixel-wise measurement guarantees the accuracy of a system and (3) understanding the damage of constructions from any pre-selected points is a mandatary requirement. To address these problems, we propose a cascade Principal Component Analysis (PCA) to efficiently measure crack width from images. Firstly, the binary crack image is obtained to describe the crack via the off-the-shelf crack detection algorithms. Secondly, given a pre-selected point, PCA is used to find the main axis of a crack. Thirdly, Robust Principal Component Analysis (RPCA) is proposed to compute the main axis of a crack with a irregular boundary. We evaluate the proposed method on a real data set. The experimental results show that the proposed method achieves the state-of-the-art performances in terms of efficiency and effectiveness. © 2018 Association for Computing Machinery.
Keyword ：
Measurement Measurement Principal component analysis Principal component analysis Cascades (fluid mechanics) Cascades (fluid mechanics) Robust control Robust control Binary images Binary images Crack detection Crack detection
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| GB/T 7714 | Duan, Lijuan , Geng, Huiling , Zeng, Jun et al. Fast and accurately measuring crack width via cascade principal component analysis [C] . 2019 . |
| MLA | Duan, Lijuan et al. "Fast and accurately measuring crack width via cascade principal component analysis" . (2019) . |
| APA | Duan, Lijuan , Geng, Huiling , Zeng, Jun , Pang, Junbiao , Huang, Qingming . Fast and accurately measuring crack width via cascade principal component analysis . (2019) . |
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