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

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Reputational Genetic Model for Regular Inference 常规推理的声誉遗传模型
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373445
P. Grachev
{"title":"Reputational Genetic Model for Regular Inference","authors":"P. Grachev","doi":"10.1145/3373419.3373445","DOIUrl":"https://doi.org/10.1145/3373419.3373445","url":null,"abstract":"The regular inference is one of the main problems of the formal language theory, which is to synthesize a finite-state automaton corresponding to some unknown regular language represented with a list of positive and negative examples. In this paper, we propose a new algorithm for regular inference along with special measures for evaluating quality of elements of automaton we call reputation. The algorithm belongs to genetic algorithms family and transforms candidate automatons based on the reputation of its elements. We prove effectiveness of our model by experiments on pregenerated datasets.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"40 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":"129948420","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
Explore the Influence of Politics on Cultural Attention Based on Sentiment Analysis of Social Network Data 基于社交网络数据情感分析探讨政治对文化关注的影响
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373420
Yufan Song, Jianlu Hu, Huilin Yuan
{"title":"Explore the Influence of Politics on Cultural Attention Based on Sentiment Analysis of Social Network Data","authors":"Yufan Song, Jianlu Hu, Huilin Yuan","doi":"10.1145/3373419.3373420","DOIUrl":"https://doi.org/10.1145/3373419.3373420","url":null,"abstract":"With the increasingly frequent cultural exchanges between China and foreign countries, more and more Chinese people advocate western festivals. Foreign culture has invaded China and our traditional culture has been neglected seriously, which results in the more servere sense of loss of traditional culture. Therefore, Chinese government has stepped up efforts to spread traditional culture and issued relevant documents to make the public pay more attention to the inheritance and development of traditional culture. By mining relevant festival data in Sina Weibo which is sent before and after the policy release, this paper use Chinese word segmentation technology and naive bayes classifier to analyze the change of public sentiment value and the distribution of emotional tendency to explore whether the Policy can promote the spread of culture and the positive significance of policy for the transmission of traditional culture.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"25 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":"129538000","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
A Noise Resistant Method by Setting Thresholds for Use With Face Recognition 一种基于阈值的人脸识别抗噪方法
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373447
Yuewei Li, Yongjun Zhang, Qian Wang, Ling Xiao
{"title":"A Noise Resistant Method by Setting Thresholds for Use With Face Recognition","authors":"Yuewei Li, Yongjun Zhang, Qian Wang, Ling Xiao","doi":"10.1145/3373419.3373447","DOIUrl":"https://doi.org/10.1145/3373419.3373447","url":null,"abstract":"Face recognition is one of the important research contents of biometric recognition, and it is widely used in various fields of life. The recognized face image is acquired by devices such as video capture, and noise is generated by device factors or external influences during the acquisition process, thereby reducing the accuracy of recognition. If the noise intensity is basically fixed, the smaller the pixel value is, the larger the proportion of noise is. This pixel has low reliability for image description. Therefore, a method of noise resistant is proposed from the angle of image preprocessing to reduce the impact of this problem. This anti-noise method first sets a certain threshold. If the pixel value in the image is lower than it, the pixel values below the set value will be directly set to 0. Then, using the classification algorithm of cosine similarity, the similarity calculation is performed on the face image, so that the image is classified, finally recognized, and the results are output. The experimental results show that after the appropriate threshold is selected, the proposed method can reduce the interference of noise on the classification and improve the accuracy of face recognition.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"6 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":"127916329","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
Research on Optimizing the Support of Conscription Recruits Cloths Based on Big Data 基于大数据的征兵服保障优化研究
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373440
Chenggong Zhai, Shanbo Zhou, Gaoyang Zhang
{"title":"Research on Optimizing the Support of Conscription Recruits Cloths Based on Big Data","authors":"Chenggong Zhai, Shanbo Zhou, Gaoyang Zhang","doi":"10.1145/3373419.3373440","DOIUrl":"https://doi.org/10.1145/3373419.3373440","url":null,"abstract":"This paper mainly uses big data technology to analyze and statistics the distribution of conscription number over the years. Based on this result, the budget and preset of conscription material are made. Finally, the classification of conscription number is adjusted according to the characteristics of conscription recruits and the feedback of conscription distribution.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"20 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":"125071340","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
Automatic Classification of Glaciers from Sentinel-2 Imagery Using A Novel Deep Learning Model 基于新型深度学习模型的Sentinel-2图像冰川自动分类
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373460
Shuai Yan, Linlin Xu, Rui Wu
{"title":"Automatic Classification of Glaciers from Sentinel-2 Imagery Using A Novel Deep Learning Model","authors":"Shuai Yan, Linlin Xu, Rui Wu","doi":"10.1145/3373419.3373460","DOIUrl":"https://doi.org/10.1145/3373419.3373460","url":null,"abstract":"The Sentinel-2 imagery provides accessible multispectral imagery, allowing better operation monitoring of glacier for climate change research, sea level rise and human life. Nevertheless, automatic glacial classification from Sentinel-2 is a challenging due to factors such as complex environment, different resolution bands and noisy or correlation in the spectral or spatial domain. In this paper, we propose an automatic glacier discrimination approach named MSSUnet to address several key research issues. First, a spatial-spectral module is used to adaptively learning the feature from different spectral band and neighboring pixels, which can better learn spatial-spectral features and reduce the impact of noise. Second, a band fusion method is applied to achieve fusion of different resolution bands in Sentinel-2 and reduce the interference of additional information. Furthermore, the proposed MSSUNet is compared with several existing neural networks on Sentinel-2 imagery to justify the advantage and improvement of the proposed approach. Experimental results show the improved performance of our proposed network over the other approaches.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"12 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":"127832007","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
Marker Based Pedestrian Detection Using Augmented Reality 利用增强现实技术进行基于标记的行人检测
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373456
C. Kim, Hyojin Kim, Huiseung Son, Muhammad Tanseef Shahid, H. Song, F. Piccialli, K. Choi
{"title":"Marker Based Pedestrian Detection Using Augmented Reality","authors":"C. Kim, Hyojin Kim, Huiseung Son, Muhammad Tanseef Shahid, H. Song, F. Piccialli, K. Choi","doi":"10.1145/3373419.3373456","DOIUrl":"https://doi.org/10.1145/3373419.3373456","url":null,"abstract":"Pedestrian detection is a popular research topic from the last decade. Most of the pedestrian identification models are based on face recognition algorithms. It is a difficult task to detect and track individual pedestrians based on these algorithms because there is a compulsion that their faces should be towards the camera. This limitation makes face recognition algorithms inefficient to detect pedestrians from the backsides. In this paper, we proposed a method for pedestrian detection using marker recognition. Multiple pedestrians are detected and then tracked based on markers attached to their backsides. Attaching markers on back-side of pedestrians helps to recognize them even when they are looking the other way. After the marker is recognized, the unique character related to that marker is displayed as a 3D object. This marker-based pedestrian detection is carried out using a mobile phone system and can be applied to embedded systems. The proposed method makes it possible to recognize up to three pedestrians located at different positions from the camera.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"46 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":"127484439","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
Health Risk Assessment Model of Drinking Water Sources Based on Combination of Bayesian and Triangle Fuzzy Number 基于贝叶斯与三角模糊数结合的饮用水源地健康风险评价模型
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373432
Weijian Ran, Xin Tian, Yumin Wang
{"title":"Health Risk Assessment Model of Drinking Water Sources Based on Combination of Bayesian and Triangle Fuzzy Number","authors":"Weijian Ran, Xin Tian, Yumin Wang","doi":"10.1145/3373419.3373432","DOIUrl":"https://doi.org/10.1145/3373419.3373432","url":null,"abstract":"Health risk assessment of water sources simulates the relationship between water quality and human health quantitatively. In this paper, fuzzy-Bayesian water environment health risk assessment model was developed based on fuzzy theory and Bayesian approach. The model proposed was applied to simulate two surface water sources in a certain city to assess the water environment health risk. The results indicated that the Cr (VI) was the biggest factor influencing the individual annual health risk. Compared with Cr (VI), the effect of As was relatively smaller. The effects of non-carcinogenic chemical toxicants on annual health risk level could be ignored which were so minor compared with Cr and As. In addition, the health risk levels of two water sources were of level VI and level VI, respectively.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"20 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":"115695528","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
KNN-LOF Algorithm Based on Skew Detection and Correction for Myanmar Handwritten Documents 基于KNN-LOF算法的缅甸语手写文档偏斜检测与校正
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373446
Chit San Lwin, Xiangqian Wu
{"title":"KNN-LOF Algorithm Based on Skew Detection and Correction for Myanmar Handwritten Documents","authors":"Chit San Lwin, Xiangqian Wu","doi":"10.1145/3373419.3373446","DOIUrl":"https://doi.org/10.1145/3373419.3373446","url":null,"abstract":"Skew detection and correction play key roles in helping character recognition processes to achieve more accurate recognition results. In this paper, we bring the idea of detection of outlier into detection skewness of Myanmar handwritten characters in printed documents. For this purpose, we present a novel detection and correction algorithm based on the k-nearest neighbor-local outlier factors algorithm. The aim is to detect local skewness that quite happens in the human's handwritten process which is in the form of fluctuation in written lines of text. Based on local skewness detection, we detect and further correct global skewness of input character image. In order to reveal the efficiency and performance of the proposed algorithm, we first prepare the datasets composed of different handwritten styles with various fonts and skew angles. We afterward perform experiments to witness how this proposed algorithm can perform well in local and global skewness detection and correction in Myanmar handwritten documents. The results show that we achieve better results in different experimental settings.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"72 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":"132656313","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
A Novel Local Feature Extraction Algorithm Based on Gabor Wavelet Transform 一种基于Gabor小波变换的局部特征提取算法
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373452
Jin Liu, Zilu Wu, Qi Li, Qiang Pu
{"title":"A Novel Local Feature Extraction Algorithm Based on Gabor Wavelet Transform","authors":"Jin Liu, Zilu Wu, Qi Li, Qiang Pu","doi":"10.1145/3373419.3373452","DOIUrl":"https://doi.org/10.1145/3373419.3373452","url":null,"abstract":"Aiming at the problem that the feature extraction method based on Gabor wavelet transform makes the feature vector dimension higher, a novel method named GCLBP (Gabor-CSLBP) is proposed in this paper. Based on Gabor wavelet transform, the proposed algorithm is a local feature extraction method, which extracted a new kind of feature through applying the idea of CS-LBP (Center-Symmetric Local Binary Pattern) into the resulted sub-images of Gabor transform. The feature vector obtained by the GCLBP method combines the advantages of Gabor wavelet transform and CS-LBP, which not only reduces the dimension of the feature vector, but also improves the robustness of image variation. The proposed method is evaluated by extensive experiments on benchmark databases CMU PIE, and Extended Yale B. The experimental results show that the proposed method -- GCLBP, can significantly improve the face recognition rate under complex illumination.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"116 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":"134512136","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
The Downscaling of the SMOS Global Sea Surface Salinity Product Based on MODIS Data Using a Deep Convolution Network Approach 基于MODIS数据的SMOS全球海面盐度产品的深度卷积网络降尺度研究
Proceedings of the 2019 3rd International Conference on Advances in Image Processing Pub Date : 2019-11-08 DOI: 10.1145/3373419.3373462
Qixin Liu, Linlin Xu, Zhiwen Zhang
{"title":"The Downscaling of the SMOS Global Sea Surface Salinity Product Based on MODIS Data Using a Deep Convolution Network Approach","authors":"Qixin Liu, Linlin Xu, Zhiwen Zhang","doi":"10.1145/3373419.3373462","DOIUrl":"https://doi.org/10.1145/3373419.3373462","url":null,"abstract":"Downscaling is a very important process to convert a coarse domain satellite product to a finer spatial resolution. In this paper, a deep learning based downscaling method was designed to improve the spatial resolution of the global sea surface salinity (SSS) products of Soil Moisture and Ocean Salinity (SMOS) satellite. The proposed algorithm is able to efficiently and effectively use high spatial-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data to improve the spatial resolution of SMOS SSS products.","PeriodicalId":352528,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Advances in Image Processing","volume":"16 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":"134232591","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
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