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学者姓名：侯义斌
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Abstract ：
针对无人驾驶汽车自动识别连续交警手势的需求,提出高度分层分区的图卷积交警手势识别方法.首先,依据人体部件在空间域内的自然、辅助和自身连接关系以及时间域内的关联关系建立交警手势时空图模型,并从图像序列卷积预测模型参数;其次,引入时空图卷积网络,提出以人物自然站立状态下时空图顶点相对高度差为标签的图卷积高度分层分区策略,打破现有分区策略对图结构的限制;最后,设计保留时间维度的空间域平均层网络输出架构,在减少特征数量的同时适配多对多序列预测模式,达到识别连续交警手势的目的.与领域内代表性方法的对比实验表明,该方法的识别准确率显著提高,不同手势之间混淆率仅为0.1%, Jaccard指数超过对比方法.
Keyword ：
图卷积 图卷积 连续手势 连续手势 交警手势 交警手势 时空图 时空图 手势识别 手势识别
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| GB/T 7714 | 张丞 , 侯义斌 , 何坚 . 高度分层分区的图卷积交警手势识别技术 [J]. | 计算机辅助设计与图形学学报 , 2022 , 34 (07) : 1037-1046 . |
| MLA | 张丞 等. "高度分层分区的图卷积交警手势识别技术" . | 计算机辅助设计与图形学学报 34 . 07 (2022) : 1037-1046 . |
| APA | 张丞 , 侯义斌 , 何坚 . 高度分层分区的图卷积交警手势识别技术 . | 计算机辅助设计与图形学学报 , 2022 , 34 (07) , 1037-1046 . |
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Abstract ：
A fall detection module is an important component of community-based care for the elderly to reduce their health risk. It requires the accuracy of detections as well as maintains energy saving. In order to meet the above requirements, a sensing module-integrated energy-efficient sensor was developed which can sense and cache the data of human activity in sleep mode, and an interrupt-driven algorithm is proposed to transmit the data to a server integrated with ZigBee. Secondly, a deep neural network for fall detection (FD-DNN) running on the server is carefully designed to detect falls accurately. FD-DNN, which combines the convolutional neural networks (CNN) with long short-term memory (LSTM) algorithms, was tested on both with online and offline datasets. The experimental result shows that it takes advantage of CNN and LSTM, and achieved 99.17% fall detection accuracy, while its specificity and sensitivity are 99.94% and 94.09%, respectively. Meanwhile, it has the characteristics of low power consumption.
Keyword ：
energy-efficient energy-efficient fall detection fall detection FD-DNN FD-DNN ZigBee ZigBee
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| GB/T 7714 | Liu, Leyuan , Hou, Yibin , He, Jian et al. An Energy-Efficient Fall Detection Method Based on FD-DNN for Elderly People [J]. | SENSORS , 2020 , 20 (15) . |
| MLA | Liu, Leyuan et al. "An Energy-Efficient Fall Detection Method Based on FD-DNN for Elderly People" . | SENSORS 20 . 15 (2020) . |
| APA | Liu, Leyuan , Hou, Yibin , He, Jian , Lungu, Jonathan , Dong, Ruihai . An Energy-Efficient Fall Detection Method Based on FD-DNN for Elderly People . | SENSORS , 2020 , 20 (15) . |
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Abstract ：
The bus passenger data are very important for urban bus dispatching management. When passengers get on or off the bus, they often hide from each other. It is a great challenge for automatically accounting passengers through camera. The traditionally video-based target detection algorithm or target tracking algorithm is difficult to accurately count the number of passenger on and off. In this paper, the YOLOv2 algorithm is combined with the MIL tracker so as to real-time account the number of passengers in the bus surveillance video. Experiment shows that the accuracy rate of bus passenger statistics proposed in this paper reaches over 99%, and it proves that our method has good real-time and high accuracy. © 2020 IEEE.
Keyword ：
Buses Buses Security systems Security systems Target tracking Target tracking
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| GB/T 7714 | Liu, Leyuan , He, Jian , Hou, Yibin et al. A Technology for Automatically Counting Bus Passenger Based on YOLOv2 and MIL Algorithm [C] . 2020 : 166-170 . |
| MLA | Liu, Leyuan et al. "A Technology for Automatically Counting Bus Passenger Based on YOLOv2 and MIL Algorithm" . (2020) : 166-170 . |
| APA | Liu, Leyuan , He, Jian , Hou, Yibin , Zhang, Cheng . A Technology for Automatically Counting Bus Passenger Based on YOLOv2 and MIL Algorithm . (2020) : 166-170 . |
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Abstract ：
The purpose of the study is to evaluate the quality of computer video image quality under the Internet of things, so as to improve the user's quality of experience. The research method is studied with MATLAB 2017 software and NS2+cygwin and MyEvalvid and visio 2016 software. The result is that the Logistic function can be used to get the subjective and an objective fitting map, Logistic function is better than other function under the field of video image quality evaluation under the Internet of things. The conclusion is that the method of video image quality evaluation model under the Internet of things is proposed in the paper is more accurate and faster than the other methods. Because coefficient SROCC, KROCC, PLCC, RMSE is close to 1, so the model has good performance. Access control card recognition, vehicle recognition, license plate recognition, intelligent transportation and IPTV and computer are all applications of the Internet of things. © 2019 IEEE.
Keyword ：
Optical character recognition Optical character recognition Function evaluation Function evaluation MATLAB MATLAB Quality of service Quality of service Quality control Quality control Image enhancement Image enhancement IPTV IPTV Access control Access control User experience User experience Internet of things Internet of things License plates (automobile) License plates (automobile) Image quality Image quality
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| GB/T 7714 | Hou, Yibin , Wang, Jin . Evaluation Model of Computer Video Image Quality under the Internet of Things [C] . 2019 : 552-563 . |
| MLA | Hou, Yibin et al. "Evaluation Model of Computer Video Image Quality under the Internet of Things" . (2019) : 552-563 . |
| APA | Hou, Yibin , Wang, Jin . Evaluation Model of Computer Video Image Quality under the Internet of Things . (2019) : 552-563 . |
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Abstract ：
物联网和网络视频丢包率到用户体验质量的映射模型是学术界和工商界的热点话题。为了研究视频在网络传输过程中丢包对QoE的影响并建立丢包率到QoE的映射，搭建了NS2 + MyEvalvid实验仿真平台，重点研究丢包对用户体验质量QoE的影响并建立丢包率到用户体验质量QoE的映射。仿真结果表明，丢包对用户体验质量QoE有着显著影响，丢包率和用户体验质量QoE呈现一元非线性关系。因此，在研究丢包对QoE有显著影响的基础上，采用一元非线性回归分析的方法建立丢包率到用户体验质量QoE的映射。
Keyword ：
Influence Influence Mapping Model Mapping Model Packet Loss Rate Packet Loss Rate 影响 影响 Quality of Experience Quality of Experience 丢包率 丢包率 用户体验质量 用户体验质量 丢包 丢包 Packet Loss Packet Loss 映射模型 映射模型 Network Video Network Video 网络视频M 网络视频M
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| GB/T 7714 | 侯义斌 , 王进 . 物联网下网络视频丢包率到用户体验质量的数学映射模型 [J]. | 软件工程与应用 , 2019 , 8 (03) : 131-140 . |
| MLA | 侯义斌 et al. "物联网下网络视频丢包率到用户体验质量的数学映射模型" . | 软件工程与应用 8 . 03 (2019) : 131-140 . |
| APA | 侯义斌 , 王进 . 物联网下网络视频丢包率到用户体验质量的数学映射模型 . | 软件工程与应用 , 2019 , 8 (03) , 131-140 . |
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Abstract ：
物联网和网络视频丢包率到用户体验质量的映射模型是学术界和工商界的热点话题。为了更好地建立考虑网络丢包的视频质量无参评估模型得到更好的QoE评价，通过建立cygwin + NS2的网络环境对网络中丢包的尺度特性进行研究，丢包的尺度特性通过影响丢包率来影响QoE。实验结果表明，丢包的过程具有长相关性，叠加源个数N，形状参数和Hurst参数以及输出链路速度都可以影响丢包的长相关性。得出的结论是叠加源个数越多，形状参数越小，Hurst参数越大，输出链路速度越小，则丢包的长相关性越大，丢包率越大。
Keyword ：
Quality Assessment Model Quality Assessment Model No-Reference No-Reference 长相关性丢包 长相关性丢包 Network Packet Loss Network Packet Loss Long-Range Dependence Long-Range Dependence 质量评估模型 质量评估模型 The Long Phase of Network Packet Loss The Long Phase of Network Packet Loss 网络丢包 网络丢包 网络丢包的长相关性 网络丢包的长相关性 无参考 无参考
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| GB/T 7714 | 侯义斌 , 王进 . 物联网下影响网络丢包的长相关性的因素对丢包率的影响 [J]. | 软件工程与应用 , 2019 , 8 (03) : 121-130 . |
| MLA | 侯义斌 et al. "物联网下影响网络丢包的长相关性的因素对丢包率的影响" . | 软件工程与应用 8 . 03 (2019) : 121-130 . |
| APA | 侯义斌 , 王进 . 物联网下影响网络丢包的长相关性的因素对丢包率的影响 . | 软件工程与应用 , 2019 , 8 (03) , 121-130 . |
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Abstract ：
Big data to use JAVA, group software engineering, networking, cloud computing knowledge and technology. The purpose of this paper is Research on Wireless sensor network of the Internet of things. The Internet of things, mainly includes multicast network, ZIGBEE network, WSN network, Bluetooth network, infrared network and so on. Swarm software engineering is a way to implement cloud computing, Internet of things and big data. Cloud computing comes from big data, the Internet of things can be achieved through cloud computing. This paper mainly studies, computers, software, networks, smart cities, and the use of Excel and Matlab and Microsoft Office Visio 2003 mapping and so forth. And through the practice of research methods, including automotive networking and smart city. What is the Internet of things, objects connected to the Internet is the Internet of things, cup networking, car networking. Things better than other networks, is composed of what objects, what composition, what nature, what innovation and superiority. The four key technologies of the Internet are widely used, and these four technologies are mainly RFID, WSN, M2M, two kinds of integration. RFID can be implemented using MATLAB, NS2, and JAVA, and WSN can be implemented using NS2, and M2M can be developed using JAVA. The research results are that the Internet of things originated and developed in the Internet; on the contrary, the development of the Internet of things further promoted the Internet to a more widespread 'Internet' evolution. The Internet of things and the Internet are the relationships between the parent and the child. Wireless networks are just like wireless WSN networks, but wireless nodes are fixed and moved into sensors. The Internet of things includes Internet technology, including wired and wireless networks. The research conclusion is the wireless internet of things are just like the wired internet of things, wired provides the basis for Wireless Research. Baidu Tiangong Internet of things platform, Amazon AWS platform, ERP and so on are also important applications of the Internet of things. The use of mirroring and replication software also requires Internet of things. Video is composed of multi frame images. H.264 and JM encoder are also the future directions. Where to go network Ctrip network is the application of the Internet of things. Recalling what we do today, planning tomorrow, how to spend the university stage and predicting the future of university development can be the application of the Internet of things. I visited the Tangshan Rd. Mart store in Qian’an from January 2017 to March. The feeling is that Beijing is still Carrefour and Jing Kelong and WAL-MART and Hualian. The electricity supplier which Ma Yun’s Alibaba still feels more powerful. Now Hebei province and all parts of the country have venture capital and subsidy, which will undoubtedly promote the Internet of things. © Springer Nature Switzerland AG 2019.
Keyword ：
Wireless sensor networks Wireless sensor networks MATLAB MATLAB Smart city Smart city Java programming language Java programming language Investments Investments Big data Big data Cloud computing Cloud computing Zigbee Zigbee Internet of things Internet of things Electric utilities Electric utilities
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| GB/T 7714 | Hou, Yibin , Wang, Jin . Investigation of wireless sensor network of the internet of things [C] . 2019 : 21-29 . |
| MLA | Hou, Yibin et al. "Investigation of wireless sensor network of the internet of things" . (2019) : 21-29 . |
| APA | Hou, Yibin , Wang, Jin . Investigation of wireless sensor network of the internet of things . (2019) : 21-29 . |
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Abstract ：
Most existing tracking methods are hard to combine accuracy and performance, and do not consider the shift between clarity and blur that often occurs. In this paper, we propound a multi-stage tracking framework with two particular modules: position prediction and corrective measure. We conduct tracking based on correlation filter with a corrective measure module to increase both performance and accuracy. Specifically, a convolutional network is used for solving the blur problem in realistic scene, training methodology that training dataset with blur images generated by the three blur algorithms. Then, we propose a position prediction module to reduce the computation cost and make tracker more capable of fast motion. Experimental result shows that our tracking method is more robust compared to others and more accurate on the benchmark sequences.
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| GB/T 7714 | Chen, Xin , Ren, Keyan , Hou, Yibin . Multi-Stage Target Tracking with Drift Correction and Position Prediction [C] . 2018 . |
| MLA | Chen, Xin et al. "Multi-Stage Target Tracking with Drift Correction and Position Prediction" . (2018) . |
| APA | Chen, Xin , Ren, Keyan , Hou, Yibin . Multi-Stage Target Tracking with Drift Correction and Position Prediction . (2018) . |
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Abstract ：
研究无线传感器网络QOS-QOE节能优化模型的目的是界定和研究WSN网络QOS-QOE节能优化建模问题。研究内容主要是无线传感器网络QOS-QOE，第一，研究WSN网络以及其下面各种算法主要是解决TSP问题，然后研究QOE模型，建立模型参数可以包括QOS因素也可以包括非QOS因素，最后研究QOS-QOE模型，参数只包括QOS因素。研究方法主要是找到关键问题无线传感器网络QOS-QOE节能优化建模研究，通常目标函数是关键问题，主要采用蚁群算法，遗传算法，人工神经网络下SVM + PCA和LS-SVM和LIBSVM等方法。互联网的四大关键技术应用非常广泛，这四种技术主要是RFID，WSN，M2M两种融合。RFID可以使用matlab，NS2，JAVA实现，WSN可以使用NS2，OMNET++实现，M2M可以使用JAVA开发。研究结论是物联网来源和发展于互联网；反之，物联网的发展又进一步推动互联网向一种更为广泛的“互联”演进。物联网和互联网是父与子的关系，无线网络和无线WSN网络一样，只不过无线节点固定和移动的变为了传感器而已。无线传感器网络QOS-QOE节能优化模型比其他QOE模型更节能，更精确，更优化。物联网包括互联网技术，WSN网络，RFID可以是WSN网络的一部分，RFID的翅膀是WSN网络。航天科技行业也应用到了物联网。
Keyword ：
QoE QoE 遗传算法Wireless Sensor Network 遗传算法Wireless Sensor Network 无线传感器网络 无线传感器网络 Energy Saving Optimization Model Energy Saving Optimization Model Genetic Algorithm Genetic Algorithm 节能优化模型 节能优化模型 QoS QoS
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| GB/T 7714 | 侯义斌 , 王进 . 无线传感器网络QOS-QOE节能优化模型 [J]. | 传感器技术与应用 , 2018 , 6 (02) : 50-57 . |
| MLA | 侯义斌 et al. "无线传感器网络QOS-QOE节能优化模型" . | 传感器技术与应用 6 . 02 (2018) : 50-57 . |
| APA | 侯义斌 , 王进 . 无线传感器网络QOS-QOE节能优化模型 . | 传感器技术与应用 , 2018 , 6 (02) , 50-57 . |
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Abstract ：
生态自然观和科学发展观二者紧密联系。生态自然观主要是实现人与自然的和谐发展，共同进化，人是生态系统中的普通一员。科学发展观研究的基本要求和目的是实现可持续发展。研究方法是全面协调可持续发展，也就是要求人与自然协调发展，从而实现持续发展。科学发展观的根本方法是统筹兼顾，这就要求发展的同时要统筹生态这个有机体的各个方面。研究结果表明：生态自然观与中国的科学发展观二者在思想上是相一致的。研究结论：生态自然观和科学发展观都要求人类在发展的同时不要忽视生态问题，维持生态和谐，统筹各个方面，实现人与自然的和谐发展。
Keyword ：
生态自然观 生态自然观 科学发展观 科学发展观 人与自然和谐发展 人与自然和谐发展 The Harmonious Development of Man and Nature The Harmonious Development of Man and Nature Scientific Outlook on Development Scientific Outlook on Development Ecological View of Nature Ecological View of Nature The Construction of Ecological Civilization The Construction of Ecological Civilization 生态文明建设 生态文明建设
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| GB/T 7714 | 侯义斌 , 王进 . 生态自然观与科学发展观问题研究 [J]. | 社会科学前沿 , 2018 , 7 (09) : 1486-1490 . |
| MLA | 侯义斌 et al. "生态自然观与科学发展观问题研究" . | 社会科学前沿 7 . 09 (2018) : 1486-1490 . |
| APA | 侯义斌 , 王进 . 生态自然观与科学发展观问题研究 . | 社会科学前沿 , 2018 , 7 (09) , 1486-1490 . |
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