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Proceedings of the 2019 3rd International Conference on Advances in Image Processing最新文献

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Data Driven Operation Quality Evaluation for General Aviation Crew 数据驱动的通用航空机组作业质量评价
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373428
Fuqiang Xin, Huaimu Sun, Hongjun Li, D. Qiao
{"title":"Data Driven Operation Quality Evaluation for General Aviation Crew","authors":"Fuqiang Xin, Huaimu Sun, Hongjun Li, D. Qiao","doi":"10.1145/3373419.3373428","DOIUrl":"https://doi.org/10.1145/3373419.3373428","url":null,"abstract":"In order to improve the accuracy of quality evaluation in operation of navigable crew, a model of crew operation quality evaluation system based on improved entropy weight method is proposed in this paper. Firstly, the existing evaluation system of operational quality of navigation crew is processed, and important indexes are extracted to exclude the meaningless ones. Then, the weights of each index are calculated by AHP method and entropy weight method respectively. Finally, the combined weights of each index are calculated by Lagrange least multiplier method, combining with actual data. The model is used to rank and evaluate the operation of the crew. The results show that compared with the single subjective and objective empowerment method, the improved method is more comprehensive and can provide effective evidence for staff to evaluate the quality of work.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115974706","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
Feature Extraction Based on Frame Interval for Wireless Network Devices 基于帧间隔的无线网络设备特征提取
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373442
Zhibin Yu, Shuangqiu Li, Ruilun Zong
{"title":"Feature Extraction Based on Frame Interval for Wireless Network Devices","authors":"Zhibin Yu, Shuangqiu Li, Ruilun Zong","doi":"10.1145/3373419.3373442","DOIUrl":"https://doi.org/10.1145/3373419.3373442","url":null,"abstract":"The development of wireless communication technology has brought great convenience to our lives, however, in the fields of military communications, remote signal control and wireless signal transmissions, we still face huge challenges. Based on the problems above, some researchers extract features from the time domain and the frequency domain of the transient and steady-state part of the wireless signal separately, ultimately achieved the purpose of identification individual wireless network devices; some researchers extract the features of the wireless frames by parsing the IEEE802.11 protocols, and the method can also achieve the purpose of identifying wireless network devices. For the steady-state part of the wireless signal, it needs high-precision equipments for data acquisition, and the volume of data obtained is very large. As for the transient part of the wireless signal, it has a very short duration, conventional equipment can hardly meet the requirements. The method by parsing the wireless frames and then extracting the frame interval is also very inefficient, it has some limitations for parameter acquisition. In this paper, we proposed a method which takes frame interval as a fingerprint to represent wireless device, this method eliminates the need for high-precision equipments, at the same time, it avoids the demands to parse the IEEE802.11 protocols. Using this method, we can quickly and easily get data whose volume is quite small without expensive equipment. Probability density curves are used in this paper to represent the signature. The experimental results show that the proposed method is effective for the identification of IEEE802.11 wireless network devices, and the average recognition rate reaches 95%.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126613230","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
Smooth Test for Multivariate Skew-Normality 多元偏态正态的平滑检验
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373422
Yan Su, Boyuan Zhou
{"title":"Smooth Test for Multivariate Skew-Normality","authors":"Yan Su, Boyuan Zhou","doi":"10.1145/3373419.3373422","DOIUrl":"https://doi.org/10.1145/3373419.3373422","url":null,"abstract":"Based on the smooth test for uniformity on the surface of a unit sphere, a new test for multivariate skew-normality is presented. The asymptotic null distribution of the transformed sample is obtained, and a bootstrapping algorithm is given to estimate the p-value of the test statistic. By using the Anderson-Darling test, a bootstrapping procedure is provided in order to test whether the shape parameter is zero in the multivariate skew-normal distribution.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127325995","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
Psyncgan for Data Generation Application of Partially Syncronized GAN to Image and Caption Data Generation 部分同步GAN在图像和标题数据生成中的应用
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373431
Kovtun Valery, Sajjad Kamali Siahroudi, Wei Gang
{"title":"Psyncgan for Data Generation Application of Partially Syncronized GAN to Image and Caption Data Generation","authors":"Kovtun Valery, Sajjad Kamali Siahroudi, Wei Gang","doi":"10.1145/3373419.3373431","DOIUrl":"https://doi.org/10.1145/3373419.3373431","url":null,"abstract":"A common problem that is seen in most practical applications of the general machine learning algorithms is the insufficient amount of data that has been already tagged for the application in hand. The abundance of unsyncronized (untagged) data is growing exponentially, yet its useability for practical applications is limited due to the amount of time it would take to process each data entry and classify it for each specific task. PSyncGAN is a novel approach that is able to suppliment existing sets of data that are either incomplete or insufficient for practical big data and machine learning applications. In our model, we are solving two multi-modal generative problems at the same time, Image captioning and Image Generation from natural language description with a limited amount of synchronized textual descriptions and images. The benefit of such a model is that there is no strict requirement of having synchronized corpora of text and image, but can actually make heavy use of the large amounts of singular data freely available on the internet, thus to be able to train on an almost infinite amount of data, including the data generated by the model itself. The results described below are indeed very promising, and could constitute a deeper research direction. Besides being able to train on the limited amount of training data, in this paper we also show that this model can be used as a basis for various other deep generative methods that are learning data distribution correlations (both symmetric and asymmetric) as a training data extension, by providing endless training examples for each proposed training data pair.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128881229","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
An Image Processing Method Reducing Road Marking Line Edge Features for Patrol Robots Identifying Road Boundaries 一种用于巡逻机器人道路边界识别的道路标线边缘特征的图像处理方法
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373455
Shuangye Chen, Zhi Liu
{"title":"An Image Processing Method Reducing Road Marking Line Edge Features for Patrol Robots Identifying Road Boundaries","authors":"Shuangye Chen, Zhi Liu","doi":"10.1145/3373419.3373455","DOIUrl":"https://doi.org/10.1145/3373419.3373455","url":null,"abstract":"When automatic patrol robots trying to identify road boundaries through edge detection, road marking lines on the road may cause errors. In this regard, this paper proposes a method to process images base on edge detection results, and builds a system based on the method for experiments. The experimental results show that the proposed method can effectively reduce the edge features of road markings lines while preserving the edge features of real boundaries, so that robots can identify real road boundaries.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128359679","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
A Novel Image Segmentation Algorithm Based on Active Contour Model and Retinex Model 一种基于活动轮廓模型和Retinex模型的图像分割算法
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373451
Jin Liu, Jianqiao Wang, Qi Li, Miaohua Shi
{"title":"A Novel Image Segmentation Algorithm Based on Active Contour Model and Retinex Model","authors":"Jin Liu, Jianqiao Wang, Qi Li, Miaohua Shi","doi":"10.1145/3373419.3373451","DOIUrl":"https://doi.org/10.1145/3373419.3373451","url":null,"abstract":"The algorithm of active contour model is an image segmentation method based on curve evolution theory, which have great flexibility, adaptability and separation accuracy. Accurate segmentation of inhomogeneous image targets has always been a difficult issue in image segmentation field. In this paper, an improved Chan-Vese model based on local information is proposed, which utilizes both global and local image information. Combining the local binary fitting (LBF) model with the retinex model, this paper redefines the fit of the Chan-Vese model. And adding a weight coefficient, so that the fitting term adaptively calculates the respective weights of the global and local information. The experimental results on various image data show that the proposed method can achieve more accurate segmentation results.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"8 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131141721","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
Hard disk Drive Failure Prediction Challenges in Machine Learning for Multi-variate Time Series 多变量时间序列机器学习中的硬盘故障预测挑战
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373437
Jie Yu
{"title":"Hard disk Drive Failure Prediction Challenges in Machine Learning for Multi-variate Time Series","authors":"Jie Yu","doi":"10.1145/3373419.3373437","DOIUrl":"https://doi.org/10.1145/3373419.3373437","url":null,"abstract":"Hard disk drive failure prediction (HDDFP) is an active area of machine learning applications. While recent work shows very promising results with high failure recall (95%) and precision based on SMART attributes, challenges remain that call for improvement in the machine learning pipeline. This paper starts with an introduction of the topic and a summary of recent work. Some challenges applicable to the existing solutions are then illustrated with an example using Backblaze dataset and its HDDFP rule. A main result of the paper is a rigorous formulation of the HDDFP problem as a MIMO dynamic system problem to tackle the challenges. It is also shown that the general formulation can help the existing classification method by enhancing the prediction lead time requirement. Though presented in the context of the HDDFP problem, the findings and thought process are applicable to other dynamic system failure prediction, and in some degree to the IoT and time series based analytics in general.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132585556","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: 7
Prediction of Solar Radiation in Qinghai Lake Area Based on BiLSTM-Attention Method 基于BiLSTM-Attention法的青海湖地区太阳辐射预测
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373439
Zhenye Wang, Chengxu Ye, Wentao Wang, Ping Yang
{"title":"Prediction of Solar Radiation in Qinghai Lake Area Based on BiLSTM-Attention Method","authors":"Zhenye Wang, Chengxu Ye, Wentao Wang, Ping Yang","doi":"10.1145/3373419.3373439","DOIUrl":"https://doi.org/10.1145/3373419.3373439","url":null,"abstract":"Short-term solar radiation prediction plays a crucial role in production and life. There is much room for improvement in the prediction accuracy and stability of traditional models. In order to solve this problem, this paper uses a method based on deep learning to predict solar radiation. A short-term solar radiation prediction model is established for Qinghai Lake combined with a bidirectional long-term memory network and attention mechanism. Based on the historical solar radiation in the past month and the average temperature at 1.5 meters, the solar radiation prediction in the next two weeks is made prediction. The experimental results show that the prediction model combined with the bidirectional long-term memory network and the attention mechanism is superior to the traditional prediction method in predicting accuracy, convergence speed and root mean square error and average absolute error, which can effectively improve. The accuracy and stability of the short-term solar radiation prediction model in local areas.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130424698","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
Autonomous FOREX Trading Agents 自主外汇交易代理
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373436
Wang Ye, Wang Duo
{"title":"Autonomous FOREX Trading Agents","authors":"Wang Ye, Wang Duo","doi":"10.1145/3373419.3373436","DOIUrl":"https://doi.org/10.1145/3373419.3373436","url":null,"abstract":"In this paper we describe an infrastructure for implementing autonomous Forex trading agents without human supervision; the agents are based on traditional trading strategies including ARIMA+GARCH, Kalman Filter, expert system, empirical experiences, etc. the infrastructure of combined above strategies is rule based, which are capable of implementing traditional trading algorithms, rules of expert systems and empirical experiences from third parties; We used this infrastructure for four major foreign currency pairs trading, i.e. USD/JPY, USD/CHF, EUR/USD, GBP/USD, with daily historical data dated from 1st January 2003 until 31st December 2018; the simulated trading results of the agents show that the suggested infrastructure is profitable and worth further research.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133820682","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
Extraction Method with Word Distribution Enriched Deep Residual Network 基于词分布的深度残差网络提取方法
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373438
Chilong Wang, Zhixing Li, Shiya Ren, Huaming Wang, Feng Hu, Weibin Deng
{"title":"Extraction Method with Word Distribution Enriched Deep Residual Network","authors":"Chilong Wang, Zhixing Li, Shiya Ren, Huaming Wang, Feng Hu, Weibin Deng","doi":"10.1145/3373419.3373438","DOIUrl":"https://doi.org/10.1145/3373419.3373438","url":null,"abstract":"As a core task and important part of information extraction, relation extraction identifies the semantic relation between entity pairs. It plays an important role in semantic understanding of sentences and the construction of knowledge graphs. Most of the existing methods for relation extraction rely on semantic information. Furthermore, many word embedding models do not take position information into considerations. In this paper, combining with word vector representation of word embedding and words' positions, a word distribution model is proposed. It is used as the input of Residual Neural Network to train the classifier for relation extraction and Adversarial Training method is employed to reduce the impact of noise labels in training phase. The experimental results demonstrate the effectiveness of the proposed model on several datasets.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130494578","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
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