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2021 29th Signal Processing and Communications Applications Conference (SIU)最新文献

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Importance of Image Enhancement Methods for Fingerprint Recognition 图像增强方法在指纹识别中的重要性
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477891
Anil Osman Tur, Berkay Selbes, H. Öztürk, Ismail Karakaya, B. Demirel
{"title":"Importance of Image Enhancement Methods for Fingerprint Recognition","authors":"Anil Osman Tur, Berkay Selbes, H. Öztürk, Ismail Karakaya, B. Demirel","doi":"10.1109/SIU53274.2021.9477891","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477891","url":null,"abstract":"In recent years, due to the critical importance of fingerprint detection in security and criminal areas, the number and quality of the work done has been increasing. Fingerprint minutiae must be extracted correctly to be used in these studies. Many methods are suggested for extracting fingerprint minutiae. The proposal methods do not provide the desired results when applied to the raw fingerprint image. In order to have a high performance of the methods, it is necessary to ensure that the fingerprint characteristic on the input image is distinct. In this study, the contribution of applying different image enhancement techniques to fingerprint feature extraction was examined. As enhancement methods, Gabor filter enhancement, Local contrast enhancement, Gaussian Local Contrast enhancement, Short Time Fourier Transform enhancement, Texture Decomposition and Autoencoder were applied separately. The results of these methods were used in 2 different minutiae algorithms. The methods were compared on 4 different data sets according to Top-1, F1, Precision and Recall performance metrics.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114547272","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
Street Vendor Detection: Helping municipalities make decisions with actionable insights 街头小贩检测:帮助市政当局根据可操作的见解做出决策
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477788
Hatice Nur Ağba, Abdullah Tahir
{"title":"Street Vendor Detection: Helping municipalities make decisions with actionable insights","authors":"Hatice Nur Ağba, Abdullah Tahir","doi":"10.1109/SIU53274.2021.9477788","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477788","url":null,"abstract":"Street vendors are quite common in countries across the world. By the prevalence of mobile surveillance systems, increasing demand for automatic detection of street vendors for further decisions and planning by the city administrators emerged. In this paper, an object detector is developed using a MobileNet SSD object detection algorithm to detect vendors on the street. For this study images were used, however, in the future this technique could be used for real time video footage from street cameras. Since this is the first study tackling this issue, a data set was created from scratch. The accuracy achieved by the algorithm is promising considering the size of the data set and the minimal computational power available. The goal of this research is to pave the way for more work to be done in this area and help municipalities improve their decision making process regarding street vendor activities in countries like Mexico, Pakistan, China, Turkey, etc.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114708671","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
Analysis of Visual Sensory System based Edge Computing Approach in IOT 物联网中基于视觉感知系统的边缘计算方法分析
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477904
E. Şimşek, B. Özyer
{"title":"Analysis of Visual Sensory System based Edge Computing Approach in IOT","authors":"E. Şimşek, B. Özyer","doi":"10.1109/SIU53274.2021.9477904","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477904","url":null,"abstract":"Internet of Things technologies, have wide application area in daily life with Industry 4.0, interact with artificial intelligence, cloud computing and embedded systems. Internet of Things technology can be used in more comprehensive applications, supported by visual sensory systems. Due to the high processing, storage and communication requirements of visual sensory systems, problem-specific data processing architectures are used in the Internet of Things. Edge Computing means the methods process in the edge of the network instead of the server to reduce data transmission, processing and storage requirements. In this study, the storage, processing and transmission requirements of edge computing-based data processing architectures for the basic problems of visual perception such as object detection and object recognition are analyzed. The solution of the object detection or object recognition problems in the analysis was carried out in different scenarios. In these scenarios, the requirements are determined by sharing the methods used to solve the problem between the server and the IoT device. In the analysis, the requirements for pre and post processing methods, feature extraction methods and classification algorithms are used. According to the analysis results, it has been determined the scenario in image features are transmitted to the servers minimizes the general requirements.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114714055","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
Comparative Analysis of Adaptive Streaming with CBR and VBR Encoded Scalable Videos 基于CBR和VBR编码的可伸缩视频自适应流的比较分析
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477909
Mehmet Çali, Nükhet Özbek
{"title":"Comparative Analysis of Adaptive Streaming with CBR and VBR Encoded Scalable Videos","authors":"Mehmet Çali, Nükhet Özbek","doi":"10.1109/SIU53274.2021.9477909","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477909","url":null,"abstract":"Having an influence on the effective utilization of network resources, optimum video streaming in various network conditions have a significant role. Therefore, optimization studies on DASH receives considereable attention from the researchers. Although most of these studies focus on developing adaptation algorithm in the client side, the effect of decisions made during video encoding on the perceived quality cannot be underestimated. In this study, the effect of encoding mode selection on the perceived quality for scalable video coding is investigated. Streaming of videos which are encoded in CBR and VBR modes are tested with extensive network conditions by implementing three different adaptation algorithm. It is observed that VBR encoding has superior performance with a considerable margin in terms of both video stall duration and video quality switching frequency.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114728616","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
Transductive Polyhedral Conic Classifiers 传导多面体圆锥分类器
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477913
Halil Saglamlar, Hakan Cevikalp
{"title":"Transductive Polyhedral Conic Classifiers","authors":"Halil Saglamlar, Hakan Cevikalp","doi":"10.1109/SIU53274.2021.9477913","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477913","url":null,"abstract":"In this study, transductive (semi-supervised) polyhedral conic classifiers are proposed. In the proposed method, concave-convex procedure is used to solve the optimization problem as in Robust Transductive Support Vector Machines. This procedure decomposes a non-convex optimization problem into concave and convex parts. Unlike RTSVM that uses SVM formulation, our proposed method uses polyhedral conic classifiers (PCC) that provides tight and closed decision boundaries compared to SVM. In this way, effective, fast and better results can be obtained in large-scale datasets.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115095633","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
Prediction of Mortality and Length of Stay with Deep Learning 用深度学习预测死亡率和住院时间
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477707
Batuhan Bardak, Mehmet Tan
{"title":"Prediction of Mortality and Length of Stay with Deep Learning","authors":"Batuhan Bardak, Mehmet Tan","doi":"10.1109/SIU53274.2021.9477707","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477707","url":null,"abstract":"Predicting the mortality and the length of stay of patients during ICU stay is important for better acute care and planning of ICU resources. The recent advancements in deep learning and with the Electronic Health Record data becoming available for researchers, there has been an increasing interest in the healthcare domain. While patient's structural data are frequently used, most of the studies in the literature do not use the clinical notes due to the complex nature. In this study, we use the clinical notes besides time-series features to improve our predictions. The results have shown that the proposed deep learning based multimodal approach outperforms on all clinical tasks over baseline models.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116893551","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
Ship Transit Time Estimation (In English) 船舶过境时间估计(英文)
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477820
Özlem Er, Oguzhan Can, Yusuf Kunt
{"title":"Ship Transit Time Estimation (In English)","authors":"Özlem Er, Oguzhan Can, Yusuf Kunt","doi":"10.1109/SIU53274.2021.9477820","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477820","url":null,"abstract":"In this study, a new approach is taken to calculate ship transit time, which is an important factor in regulating maritime traffic flow. In order to predict the transit times of ships passing through a water channel, the collected Automatic Identification System signal was processed and an approach to create a dataset was demonstrated and the transition time estimation was made with the regression-based machine learning method Gradient Boosting algorithm. Resampling procedures were applied on the data set in order to balance the data based on the ship types. Ship transit time estimation mean absolute error for cargo and tanker ships was reduced from 12.84 minutes to 8.19 minutes.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117331532","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
Square Spiral Conformal Antenna Design for Capsule Endoscopy 胶囊内窥镜方形螺旋共形天线设计
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477797
Furkan Salih Yamak, Ö. Özdemir
{"title":"Square Spiral Conformal Antenna Design for Capsule Endoscopy","authors":"Furkan Salih Yamak, Ö. Özdemir","doi":"10.1109/SIU53274.2021.9477797","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477797","url":null,"abstract":"In this study, a square spiral conformal antenna design operating in the 433 MHz (ISM) band to be used in wireless capsule endoscopy applications has been designed. Antenna characteristics have been studied for different environments of the body and have been shown to antenna be workable in all environments. In order to test the data transmission between the capsule and the receiver unit located outside the human body, the S21 parameter simulations were carried out using the dipole antenna as the receiving antenna. It has been shown that the designed antenna is suitable for capsule endoscopy applications with the obtained data transmission and antenna parameters.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124032813","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
Tree-Structured Binary Neural Networks 树状结构二元神经网络
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477811
Ayse Serbetci, Y. S. Akgul
{"title":"Tree-Structured Binary Neural Networks","authors":"Ayse Serbetci, Y. S. Akgul","doi":"10.1109/SIU53274.2021.9477811","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477811","url":null,"abstract":"Deep Neural Networks are resource-intensive learning models. To enable their training and deployment on low-end devices, decreasing their computational requirements has become an attractive research area in recent years. One of the most promising approaches in this field is designing networks which use only binary values for the network weights and activations, i.e., Binary Neural Networks (BNN). However, BNNs have robustness and stability issues, which make their training difficult and BNNs perform considerably worse than their real-valued counterparts. To improve the training and deployment performance of BNNs, in this work, we employ a tree-structured network model, which has been widely used in Deep Neural Networks (DNN). We perform experiments to analyze the accuracy, stability and robustness of the proposed tree-structured BNN model. Tree-structured network model integrates multiple classifiers on a backbone BNN resulting in a multi-branch architecture. Our experiments demonstrates that tree-structures model improves the accuracy, stability and robustness of BNNs.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129908945","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
Mathematical Modeling of Threats in Electronic Warfare Systems 电子战系统中威胁的数学建模
2021 29th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2021-06-09 DOI: 10.1109/SIU53274.2021.9477995
Elif Ayyüce Muslu, Ömer Karal
{"title":"Mathematical Modeling of Threats in Electronic Warfare Systems","authors":"Elif Ayyüce Muslu, Ömer Karal","doi":"10.1109/SIU53274.2021.9477995","DOIUrl":"https://doi.org/10.1109/SIU53274.2021.9477995","url":null,"abstract":"The recent importance of simulation and modeling in Electronic Warfare Systems arises from its providing test an training opportunities without expenses and danger. In all known studies about EW simulation, only signal parameters such as radio frequency, pulse repetition interval, pulse width are used when modeling a threat. However, a real threat has maneuverability in 3D space. In this study, a threat platform modeling application in MATLAB is presented. Threat platforms and their antenna scan types (steady scan, circular scan, sectoral scan, raster scan, helical scan, scan, lobe switching) are expressed mathematically in 3-dimensional space using Euler Angles. The maneuvers of the threat platform are modeled using Rotation Matrices. By collecting the signals emitted by a threat in moving and fixed positions separately by the friendly platform, the differences between amplitude and phase values, which are important for direction finding and antenna scanning type detection algorithms, have been examined and the importance of maneuverability in a modeling has been proven.","PeriodicalId":160693,"journal":{"name":"2021 29th Signal Processing and Communications Applications Conference (SIU)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128718773","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
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