2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)最新文献_第2页

A Uniform Beam Selection Algorithm for Beamspace Mimo-Noma in Millimeter-Wave Communication System 毫米波通信系统波束空间Mimo-Noma的均匀波束选择算法

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632567

Kai-Fu Yang, Xiao Yan, Kaiyu Qin, Qian Wang

引用次数: 3

Shadow Puppetry Classification Using Convolutional Neural Networks 基于卷积神经网络的皮影戏分类

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632562

MingYun He, Xinhao Song, Ping Kuang, Fan Li, Haoshuang Wang

引用次数: 1

Analysis of the Influence of the Loop Filter in the Phase Locked Loop on the Output Phase Noise 锁相环中环路滤波器对输出相位噪声的影响分析

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632591

Yao Han, Qi Zhang, Cheng-Ke Li, Xiao-Di Li

引用次数: 2

Ws2 Switch Turned on/Off by Polarized Optical Stark Effect 偏振光斯塔克效应打开/关闭Ws2开关

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632596

Mahnoor Shahzadi, W. Zhand, A. Haq

引用次数: 0

The Cloud Resource Load Security Detection Based on Wavelet Packet Transform and Grey Wolf Algorithm 基于小波包变换和灰狼算法的云资源负载安全检测

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632600

He-Jun Jiao, Jianping Li, Tian-Chao Jiang

引用次数: 0

Improving Recommendation Performance in Matrix Factorization with Interest Exploring 利用兴趣探索改进矩阵分解的推荐性能

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632581

Wang Zhou, Jianping Li, R. Wu, Yanan Lu, Yujun Yang

引用次数: 0

Feature Fusing of Feature Pyramid Network for Multi-Scale Pedestrian Detection 多尺度行人检测中特征金字塔网络的特征融合

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632614

Fiseha B. Tesema, Junpeng Lin, Jie Ou, Hong Wu, William Zhu

{"title":"Feature Fusing of Feature Pyramid Network for Multi-Scale Pedestrian Detection","authors":"Fiseha B. Tesema, Junpeng Lin, Jie Ou, Hong Wu, William Zhu","doi":"10.1109/ICCWAMTIP.2018.8632614","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2018.8632614","url":null,"abstract":"Pedestrian detection is a fundamental component in many real-world applications such as automatic driving, intelligent surveillance, person re-identification and robotics. Therefore, it has attracted massive attention in the last decades. However, pedestrians in an images always exhibit different scales, which constitutes a significant mode of intra-class variability and affect the performance of pedestrian detection algorithm. To address this problem, we apply FPN (Feature Pyramid Network)for pedestrian detection. FPN exploits the inherent multi-scale structure of a deep convolutional network to construct a feature pyramid that has rich semantics at all levels and facilitates the detection of objects at different scales. To leverage the information from different levels of the feature pyramid, we extend the FPN-based pedestrian detection by fusing the feature of each level with adaptive feature pooling. Furthermore, we also integrate a Squeeze and Excitation module to the ROI pooled features from each level before the feature fusion. The experiment result on Caltech dataset shows that our approach outperforms the basic FPN-based pedestrian detection and robust towards to various scale of pedestrian.","PeriodicalId":117919,"journal":{"name":"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133935660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Deep Transfer Learning for Power Substation Recognition with Google Earth 基于Google Earth的变电站识别深度迁移学习

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632585

Jing Peng, Yong-Bo Liu, Yima, Yong He, Ze-zhong Zheng, Yameng Zhang, Jiang Li

{"title":"Deep Transfer Learning for Power Substation Recognition with Google Earth","authors":"Jing Peng, Yong-Bo Liu, Yima, Yong He, Ze-zhong Zheng, Yameng Zhang, Jiang Li","doi":"10.1109/ICCWAMTIP.2018.8632585","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2018.8632585","url":null,"abstract":"Power substation is a vital component of power transmission systems. However, their location information, longitude and latitude, maybe incorrect due to human errors. For example, an employee of a power grid company may carelessly input wrong location information to the system database. In practice, these errors residue in database and are difficult to be corrected or even unaware of because human naturally are insensitive to these long numbers. Correct location information is critical and it will ensure destroyed power substations to be quickly pinpointed and repaired after earthquake. In this paper, we develop a deep transfer learning approach to automatically verify power substation location information based upon Google Earth (GE)images. We first extract an image patch for a substation from GE using the recorded location information in database. We then apply the deep transfer learning model to verify whether the image patch contains a power substation. We validated the proposed method on more than 1000 substations in Yunnan Electric Power Grid. Our experimental results showed that the Xception deep transfer model achieved the best accuracy of 98.5% among four compared machine learning methods with an image size of 299⨯299 pixels. The developed model is a promising tool to verify the location information of power substations in database.","PeriodicalId":117919,"journal":{"name":"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"33 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113976120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Initialization Method of B-Spline Transformation for Medical Atlases Alignment 医学地图集对齐的b样条变换初始化方法

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632571

Zhensong Wang, Xiaoyun Liu, Wufan Chen

{"title":"An Initialization Method of B-Spline Transformation for Medical Atlases Alignment","authors":"Zhensong Wang, Xiaoyun Liu, Wufan Chen","doi":"10.1109/ICCWAMTIP.2018.8632571","DOIUrl":"https://doi.org/10.1109/ICCWAMTIP.2018.8632571","url":null,"abstract":"Atlases are widely used in medical image processing, especially in the case of image analysis based on machine learning. Spatial alignment between atlases is an essential step for these image processing tasks. The target of spatial alignment of atlases is to find an optimal spatial transformation that best aligns the structures of interest in the input images. For the case of medical image processing, due to strong ability of simulating non-rigid deformation, B-splines transformation model has been widely used. The goal of finding optimal spatial transformation is usually achieved by optimisation method. Before the optimisation starts to search for the optimal spatial transformation, an initialization of the spatial transformation model must be specified. This initialization has important influence to the searching procedure and result. A bad initialization will greatly increase search time and even more make searching algorithm converge to local minimum and then get an incorrect result. In this paper, a novel initialization method of B-spline transformation is proposed to improve the alignment of medical atlases. Specifically, the information in label images, which is neglected in conventional atlases alignment method, is used to generate an initial displacement field and then the initial displacement field is convert to parameters of B-splines transformation model. Experimental results show that our initialization approach can greatly enhance the robustness of atlases alignment method.","PeriodicalId":117919,"journal":{"name":"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"122 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129124527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Cloud Parameters Specification and Scheduling Optimization on Multidimensional Qos Constraints 基于多维Qos约束的云参数规范与调度优化

2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) Pub Date : 2018-12-01 DOI: 10.1109/ICCWAMTIP.2018.8632608

He-Jun Jiao, Jing Li, Jianping Li

引用次数: 2