Proceedings of the 3rd International Conference on Vision, Image and Signal Processing最新文献_第8页

FCCA: A New Method of Constructing Causality Network Based on Graph Structure Information and Conditional Causality Test FCCA:一种基于图结构信息和条件因果检验构建因果网络的新方法

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387208

Jiachen Liu, Junhui Gao

{"title":"FCCA: A New Method of Constructing Causality Network Based on Graph Structure Information and Conditional Causality Test","authors":"Jiachen Liu, Junhui Gao","doi":"10.1145/3387168.3387208","DOIUrl":"https://doi.org/10.1145/3387168.3387208","url":null,"abstract":"Pairwise granger causality test, which detects the causal connectivity between two nodes in a graph, has been widely used in various fields since it was proposed by economist Granger in 1969. However, pairwise granger causality test has the drawback of generating false positive causality, which is an indirect causal influence between two nodes mediated through a third node. In 1984, Geweke proposed the conditional Granger causality model, which enabled the model to eliminate false positive causal connectivity and accurately identify the causal relationships between two nodes in a high-dimensional dataset. The Matlab software tool GCCA realizes the calculation of conditional causality. For a given network, GCCA finds out all the triangular causal relationships (X~Y, Y~Z, X~Z) and calculates the causality among all three nodes. However, it is not necessary to calculate among all the three-node combinations as there may not be significant causal connectivity between any given two nodes. In additional, the full calculation of conditional granger causality could be slow. Here, we proposed a new test named Fast Causal Connectivity Analysis (FCCA) as a fast and approximative test for causal connectivity. We compared the performance of GCCA and FCCA using a time series fMRI dataset and showed that FCCA has acceptable accuracy and theoretically faster run time.","PeriodicalId":346739,"journal":{"name":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116652723","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

Prediction of PM10 Concentration in South Korea Using Gradient Tree Boosting Models 利用梯度树增强模型预测韩国PM10浓度

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387234

Khaula Qadeer, M. Jeon

{"title":"Prediction of PM10 Concentration in South Korea Using Gradient Tree Boosting Models","authors":"Khaula Qadeer, M. Jeon","doi":"10.1145/3387168.3387234","DOIUrl":"https://doi.org/10.1145/3387168.3387234","url":null,"abstract":"Particulate matter (PM) is a term generally used for very small particles and liquid droplets in the atmosphere. PM10 is the particle pollution with diameter less than or equal to 10 micrometers. Exposure to particle pollution is a public health hazard which leads to serious diseases such as asthma, bronchitis and even cancer; especially in elderly, children and sensitive people. It is crucial to predict the concentration of PM before-hand so that people can take precautionary measures and avoid the hazardous impact of pollution. These days the gradient boosting is one of popular methods in regression and classification tasks. In this study, we predict the PM10 concentration using Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) algorithms after combining meteorological, emission rate data and output features of Community Multi-Scale Air Quality (CMAQ) model. All the missing values are removed because handling them is quite challenging and requires feature engineering. The results show that XGBoost performs better than LightGBM in terms of prediction estimation with the RMSE of 12.846; but takes longer to train and tune the model's parameters. RMSE of LightGBM is 12.9066, which is slightly higher; but on the contrary, it is 29 times faster than XGBoost.","PeriodicalId":346739,"journal":{"name":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128830816","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: 9

Low Complexity Deep Learning for Mobile Face Expression Recognition 面向移动人脸表情识别的低复杂度深度学习

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387175

S. Cotter

引用次数: 4

Digital Self-interference Cancellation Algorithm Based on The Movable Shape Filter 基于可动形状滤波器的数字自干扰消除算法

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387245

Haolong Wu, Yuwen Wang, Xuanrui Qu

引用次数: 0

An Efficient Digital Nonlinear Self-Interference Cancellation Architecture for Full-Duplex System 全双工系统中一种有效的数字非线性自干扰抵消体系

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387222

Haolong Wu, Yuwen Wang, Xiaotao He, JingLu Song

引用次数: 0

Minimizing Urban Logistics Cost Using Crowd-Shipping 利用群体运输最小化城市物流成本

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387256

Chandra Restu Pakarti, S. Starita

引用次数: 2

Automatic Inspection Drone with Deep Learning-based Auto-tracking Camera Gimbal to Detect Defects in Power Lines 基于深度学习的自动跟踪相机框架的自动检测无人机用于检测电力线缺陷

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387176

Joon-Young Park, Seok-Tae Kim, Jae-Kyung Lee, Ji-Wan Ham, Ki‐Yong Oh

{"title":"Automatic Inspection Drone with Deep Learning-based Auto-tracking Camera Gimbal to Detect Defects in Power Lines","authors":"Joon-Young Park, Seok-Tae Kim, Jae-Kyung Lee, Ji-Wan Ham, Ki‐Yong Oh","doi":"10.1145/3387168.3387176","DOIUrl":"https://doi.org/10.1145/3387168.3387176","url":null,"abstract":"The traditional drone inspection performed by human operators is unsuited for the purpose of inspecting power transmission lines, because steel towers and their spans are too high and wide to be inspected with a 250 m line of sight. For this reason, the KEPCO Research Institute developed a new inspection drone system that can automatically fly a predetermined flight path based on the GPS coordinates of steel towers, filming a video of power transmission lines with a high definition camera and a thermal imaging camera. In this system, a camera gimbal with the cameras was still controlled by a human operator from a long distance away. When the drone approached close to a steel tower, however, the camera gimbal was often unable to be controlled and real-time video transmission for the gimbal operator was sometimes interrupted due to radio-frequency interference from steel structure and energized power conductors. To solve such a control problem in the field, we also developed an auto-tracking camera gimbal that can automatically track and photograph power facilities on the basis of Deep Learning. With the automatic gimbal, the entire inspection process can be fully automated. The effectiveness of the developed overall system was confirmed through field tests.","PeriodicalId":346739,"journal":{"name":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","volume":"36 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114220088","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

Parameter Analysis of an Existing Copper Access Network for the Optimization of VDSL Service in Rural Areas 面向农村VDSL业务优化的现有铜接入网参数分析

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387191

J. Jara, Rommel Carpio, Pablo Márquez, J. Inga-Ortega, Esteban Mendieta

{"title":"Parameter Analysis of an Existing Copper Access Network for the Optimization of VDSL Service in Rural Areas","authors":"J. Jara, Rommel Carpio, Pablo Márquez, J. Inga-Ortega, Esteban Mendieta","doi":"10.1145/3387168.3387191","DOIUrl":"https://doi.org/10.1145/3387168.3387191","url":null,"abstract":"In this paper, we present a modeling of transmission lines performed under real-world conditions to compare them with a theoretical transfer function. This model is based on the practical case of implementation for access networks \"last mile\" in rural areas, designed and implemented by National Telecommunication Corporation (CNT-Ecuador) at Azuay-Ecuador. In this sense, we review some theoretical concepts on evolution over time in xDSL technologies implemented by the company CNT-Ecuador. Then, we perform several field data analyses using measuring instruments, where electrical parameters were obtained with which we perform the modeling. In addition, it was realized an analysis and comparison of the obtained real capacities of transmission lines, against the theoretical ones by means of the Theorem of Shannon-Hertly for lines with VDSL technology. Into the outdoor tests and simulations, the data obtained allowed us to drastically correct the transfer functions of the lines in poor condition, through varying the most impacting electrical parameters. We present the results in a table with the ranges of the parameters that can be taken as reference so that a pair of copper wires operating in poor condition in rural areas, can work correctly with VDSL technology.","PeriodicalId":346739,"journal":{"name":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114376145","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

Object Tracking and Classification in Videos Using Compressive Measurements 基于压缩测量的视频目标跟踪与分类

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387188

C. Kwan

{"title":"Object Tracking and Classification in Videos Using Compressive Measurements","authors":"C. Kwan","doi":"10.1145/3387168.3387188","DOIUrl":"https://doi.org/10.1145/3387168.3387188","url":null,"abstract":"In this paper, we summarize some recent results on objective tracking and classification in infrared and low quality videos using compressive measurements. Two compressive measurement modes were investigated. One was based on subsampling of the original measurements. The other was based on coded aperture camera. It is important to emphasize that conventional trackers require the compressive measurements be reconstructed first before any tracking and classification processing steps begin. The reconstruction is time-consuming and may also lose information. Our proposed approach directly uses compressive measurements and a deep learning tracker known as You Only Look Once (YOLO), which is fast and can track multiple objects simultaneously, was used to track objects. The detected objects are then recognized using another deep learning model called residual network (ResNet). Extensive experiments using infrared videos from long distances were conducted. Results show that the proposed approach performs much better than conventional trackers, which failed to deal with compressive measurements. Instead, ResNet classifier performs better than the built-in classifier in YOLO.","PeriodicalId":346739,"journal":{"name":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121600633","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: 1

Design of a Mobile Panic Button for Older Adults for Monitoring through the ECU911 System 基于ECU911系统的老年人移动报警按钮的设计

Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Pub Date : 2019-08-26 DOI: 10.1145/3387168.3387195

J. Jara, J. Lima, C. Valdez, Marcelo Barbecho, J. P. Bermeo, D. Chacón

引用次数: 2