Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302375
Jawad Rasheed, Akhtar Jamil, Amani Yahyaoui, Ahmed Sheikh Abdullahi Madey
A continual increase in multimedia data needs a sophisticated automatic video indexing and retrieval system based on its content. This paper exploited statistical feature along with some morphological operations to detect horizontally aligned artificial textual fields in Turkish video frames, which are then extracted for content-based video indexing and retrieval system. First, projection analysis was performed to find the edges in the images and then morphological operations to convert the textual regions in images into lines. Later, false positives were eradicated by geometrical constraints and heuristics-based method. The detected candidate text regions were fed to optical character recognition (OCR) system to recognize and output the text. Finally, the recognized words were stored in database as keys for automatic content-based video indexing, which can be retrieved through provided web interface. For evaluation, a ground-truth preparation software is prepared to manually localize the text in images. Experimental results showed that our proposed method performed well on Turkish videos with overall f-measure of 95%.
{"title":"Automatic Video Indexing and Retrieval System for Turkish Videos","authors":"Jawad Rasheed, Akhtar Jamil, Amani Yahyaoui, Ahmed Sheikh Abdullahi Madey","doi":"10.1109/SIU49456.2020.9302375","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302375","url":null,"abstract":"A continual increase in multimedia data needs a sophisticated automatic video indexing and retrieval system based on its content. This paper exploited statistical feature along with some morphological operations to detect horizontally aligned artificial textual fields in Turkish video frames, which are then extracted for content-based video indexing and retrieval system. First, projection analysis was performed to find the edges in the images and then morphological operations to convert the textual regions in images into lines. Later, false positives were eradicated by geometrical constraints and heuristics-based method. The detected candidate text regions were fed to optical character recognition (OCR) system to recognize and output the text. Finally, the recognized words were stored in database as keys for automatic content-based video indexing, which can be retrieved through provided web interface. For evaluation, a ground-truth preparation software is prepared to manually localize the text in images. Experimental results showed that our proposed method performed well on Turkish videos with overall f-measure of 95%.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116045642","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302405
Musab Ramazan Akaslan, Y. Ozkazanc
Attitude determination in aircraft is a critical function both for navigation and flight control. Within the scope of this study, attitude determination by using GNSS position outputs is studied. An attitude determination system consisting of multiple GNSS receivers is designed and tested on the field. The attitude results were calculated by considering the reference lines of different lengths among GNSS receivers and the performance of the attitude computation were evaluated.
{"title":"GNSS Based Attitude Determination","authors":"Musab Ramazan Akaslan, Y. Ozkazanc","doi":"10.1109/SIU49456.2020.9302405","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302405","url":null,"abstract":"Attitude determination in aircraft is a critical function both for navigation and flight control. Within the scope of this study, attitude determination by using GNSS position outputs is studied. An attitude determination system consisting of multiple GNSS receivers is designed and tested on the field. The attitude results were calculated by considering the reference lines of different lengths among GNSS receivers and the performance of the attitude computation were evaluated.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"449 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122723912","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302288
Ozan Kara, Ibrahim Uçurmak, Ali Can Karaca, M. Güllü
Nowadays, multispectral images are acquired by many different satellites. These satellites produce a large amount of data by traveling around the world. Efficient compression of these images are important issues. In order to solve this problem, the most used method is compression of the images with JPEG2000 method. However, distortion occurs after JPEG2000 compression, especially at low bit-rates. This situation affects the performance of some applications such as change detection, classification, anomaly detection etc. In this paper, in order to overcome compression artifacts, a very deep süper-resolution approach is proposed as post-processing after JPEG2000 decompression. In the experiments, scenes of the Onera dataset that is shared in the website of IEEE GRSS DASE are used. Experimental results show that the proposed method not only increases the image quality but also improves the change detection performance.
{"title":"Reduction of JPEG2000 Compression Artifacts using Very Deep Super Resolution Approach for Multitemporal Multispectral Images","authors":"Ozan Kara, Ibrahim Uçurmak, Ali Can Karaca, M. Güllü","doi":"10.1109/SIU49456.2020.9302288","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302288","url":null,"abstract":"Nowadays, multispectral images are acquired by many different satellites. These satellites produce a large amount of data by traveling around the world. Efficient compression of these images are important issues. In order to solve this problem, the most used method is compression of the images with JPEG2000 method. However, distortion occurs after JPEG2000 compression, especially at low bit-rates. This situation affects the performance of some applications such as change detection, classification, anomaly detection etc. In this paper, in order to overcome compression artifacts, a very deep süper-resolution approach is proposed as post-processing after JPEG2000 decompression. In the experiments, scenes of the Onera dataset that is shared in the website of IEEE GRSS DASE are used. Experimental results show that the proposed method not only increases the image quality but also improves the change detection performance.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122974552","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302054
Atilla Özgür, Fatih Nar
In the last decade, deep learning architectures have provided good accuracy as they become deeper and wider in addition to other theoretical improvements. However, despite their current success, they initially faced with overfitting issue that limits their usage. The first practical and usable solution to overfitting in deep neural networks is a simple approach known as the dropout. Dropout is a regularization approach that randomly drops connections from earlier layers during training of neural nets. Dropout is a widely used technique, especially in image classification, speech recognition and natural language processing tasks, where features created by earlier layers are mostly redundant. Usage of the dropout layer in other tasks is largely unexplored. In this study, we seek an answer to question if the dropout layer is also useful for classical regression problems. A 3 layer deep learning net with a single dropout layer with various dropout levels tested on 8 real regression datasets. According to the experiments, the dropout layer does not help over fitting.
{"title":"Effect of Dropout layer on Classical Regression Problems","authors":"Atilla Özgür, Fatih Nar","doi":"10.1109/SIU49456.2020.9302054","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302054","url":null,"abstract":"In the last decade, deep learning architectures have provided good accuracy as they become deeper and wider in addition to other theoretical improvements. However, despite their current success, they initially faced with overfitting issue that limits their usage. The first practical and usable solution to overfitting in deep neural networks is a simple approach known as the dropout. Dropout is a regularization approach that randomly drops connections from earlier layers during training of neural nets. Dropout is a widely used technique, especially in image classification, speech recognition and natural language processing tasks, where features created by earlier layers are mostly redundant. Usage of the dropout layer in other tasks is largely unexplored. In this study, we seek an answer to question if the dropout layer is also useful for classical regression problems. A 3 layer deep learning net with a single dropout layer with various dropout levels tested on 8 real regression datasets. According to the experiments, the dropout layer does not help over fitting.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121906728","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302051
E. Yavuz, Önder Aydemir
Brain-computer interface (BCI) is a communication system between brain and computer. Although the results of BCI studies are relatively successful, it is still an area that needs to be improved. Recent studies show that combining multiple signal recording methods (hybrid), which compensates for each other's disadvantages, will improve the performance of the BBA system. Electroencephalography + near infrared spectroscopy (EEG+NIRS) based systems have gained importance among hybrid BCI models in recent years. In this study, it was aimed to improve the system performance by working with two-class mental arithmetic based EEG+NIRS dataset which was recorded from 29 subjects. EEG oxygenated hemoglobin and deoxygenated hemoglobin signals were extracted Higuchi fractal dimension or autoregressive method based features. The extracted features were classified by k-nearest neighborhood, linear discrimination analysis (LDA), naive Bayes, decision tree, support vector machines and random forest methods. The best classification accuracy was calculated as 94.08% on average for the hybrid model with LDA. 9.31% better result was achieved with the hybrid model compared to EEG shows that the proposed method is effective for this data set.
{"title":"Classification of Mental Arithmetic Based Hybrid EEG+NIRS Signals","authors":"E. Yavuz, Önder Aydemir","doi":"10.1109/SIU49456.2020.9302051","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302051","url":null,"abstract":"Brain-computer interface (BCI) is a communication system between brain and computer. Although the results of BCI studies are relatively successful, it is still an area that needs to be improved. Recent studies show that combining multiple signal recording methods (hybrid), which compensates for each other's disadvantages, will improve the performance of the BBA system. Electroencephalography + near infrared spectroscopy (EEG+NIRS) based systems have gained importance among hybrid BCI models in recent years. In this study, it was aimed to improve the system performance by working with two-class mental arithmetic based EEG+NIRS dataset which was recorded from 29 subjects. EEG oxygenated hemoglobin and deoxygenated hemoglobin signals were extracted Higuchi fractal dimension or autoregressive method based features. The extracted features were classified by k-nearest neighborhood, linear discrimination analysis (LDA), naive Bayes, decision tree, support vector machines and random forest methods. The best classification accuracy was calculated as 94.08% on average for the hybrid model with LDA. 9.31% better result was achieved with the hybrid model compared to EEG shows that the proposed method is effective for this data set.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116751451","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302408
Wael Zeinelabedeen, R. Uyguroglu
Antenna and communication technology play the key role in the applications of body healthcare monitoring systems. In these applications, the system should transmit data over a certain distance which include part of the human body. This paper demonstrates the variation of characteristic behavior of the human body channel according to the incident angle of electromagnetic (EM) wave on multilayered planar human tissue in the range of frequencies from 100 MHz to 10 GHz. The study includes simulations by the microwave simulation software CST for monitoring the oblique and transverse fractured bone as a new healthcare monitoring application depending on the oblique incident of EM wave.
{"title":"Characterization of human body channel for oblique incident case of plane wave in the 0.1-10 GHz frequency band for special health care monitoring application","authors":"Wael Zeinelabedeen, R. Uyguroglu","doi":"10.1109/SIU49456.2020.9302408","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302408","url":null,"abstract":"Antenna and communication technology play the key role in the applications of body healthcare monitoring systems. In these applications, the system should transmit data over a certain distance which include part of the human body. This paper demonstrates the variation of characteristic behavior of the human body channel according to the incident angle of electromagnetic (EM) wave on multilayered planar human tissue in the range of frequencies from 100 MHz to 10 GHz. The study includes simulations by the microwave simulation software CST for monitoring the oblique and transverse fractured bone as a new healthcare monitoring application depending on the oblique incident of EM wave.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129569943","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}
Statistical topic modeling aims to assign topics to documents in an unsupervised way. Latent Dirichlet Allocation (LDA) is the standard model for topic modeling. It shows good performance on document collections, documents being relatively long texts but it has poor performance on short texts. Topic modeling on short texts is on the rise due to the potential of social media. Thus, approaches that are able to find topics on short texts as well as long texts are sought. However, there is a lack of datasets that include both long and short texts which have the same ground-truth categories. In this work, we release a Turkish movie dataset which contain both short film descriptions and long subscripts where film genre can be considered as topic. Furthermore, we provide multi-label movie genre classification results using a Feed Forward Neural Network (FFNN) taking LDA document-topic or Doc2Vec dense representations.
{"title":"A Turkish Topic Modeling Dataset For Multi-label Classification of Movie Genre","authors":"Elgun Jabrayilzade, Algın Poyraz Arslan, Hasan Para, Ozan Polatbilek, Erhan Sezerer, Selma Tekir","doi":"10.1109/SIU49456.2020.9302027","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302027","url":null,"abstract":"Statistical topic modeling aims to assign topics to documents in an unsupervised way. Latent Dirichlet Allocation (LDA) is the standard model for topic modeling. It shows good performance on document collections, documents being relatively long texts but it has poor performance on short texts. Topic modeling on short texts is on the rise due to the potential of social media. Thus, approaches that are able to find topics on short texts as well as long texts are sought. However, there is a lack of datasets that include both long and short texts which have the same ground-truth categories. In this work, we release a Turkish movie dataset which contain both short film descriptions and long subscripts where film genre can be considered as topic. Furthermore, we provide multi-label movie genre classification results using a Feed Forward Neural Network (FFNN) taking LDA document-topic or Doc2Vec dense representations.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128326062","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302098
Imge Gamze Çavusoglu, Hande Alemdar, E. Onur
A covert channel is a communication method that misuses legitimate resources to bypass intrusion detection systems. They can be used to do illegal work like leaking classified (or sensitive) data or sending commands to malware bots. Network timing channels are a type of these channels that use inter-arrival times between network packets to encode the data to be sent. In this study, we worked with two types of network covert channels: Fixed Interval and Jitterbug. We were able to distinguish these channels from legitimate ones by using decision trees that use four statistical features (mean, variance, skewness, and kurtosis).
{"title":"Covert Channel Detection Using Machine Learning","authors":"Imge Gamze Çavusoglu, Hande Alemdar, E. Onur","doi":"10.1109/SIU49456.2020.9302098","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302098","url":null,"abstract":"A covert channel is a communication method that misuses legitimate resources to bypass intrusion detection systems. They can be used to do illegal work like leaking classified (or sensitive) data or sending commands to malware bots. Network timing channels are a type of these channels that use inter-arrival times between network packets to encode the data to be sent. In this study, we worked with two types of network covert channels: Fixed Interval and Jitterbug. We were able to distinguish these channels from legitimate ones by using decision trees that use four statistical features (mean, variance, skewness, and kurtosis).","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128720635","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302075
Mustafa Çaglar Güldiken, E. G. Schmidt, K. Schmidt
Modern rail-vehicles exchange a large amount of periodic data over in-vehicle communication buses such as the multifunction vehicle bus (MVB). This paper proposes several heuristic algorithms for the schedule computation on MVB and performs a comprehensive comparison of these algorithms to optimal schedules from an integer programming (ILP) formulation. As the main outcome, the paper shows that the proposed heuristics are highly beneficial when scheduling large telegram sets, where it is not possible to compute optimal schedules.
{"title":"Heuristic Algorithms for the Telegram Scheduling on MVB","authors":"Mustafa Çaglar Güldiken, E. G. Schmidt, K. Schmidt","doi":"10.1109/SIU49456.2020.9302075","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302075","url":null,"abstract":"Modern rail-vehicles exchange a large amount of periodic data over in-vehicle communication buses such as the multifunction vehicle bus (MVB). This paper proposes several heuristic algorithms for the schedule computation on MVB and performs a comprehensive comparison of these algorithms to optimal schedules from an integer programming (ILP) formulation. As the main outcome, the paper shows that the proposed heuristics are highly beneficial when scheduling large telegram sets, where it is not possible to compute optimal schedules.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128982065","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}
Pub Date : 2020-10-05DOI: 10.1109/SIU49456.2020.9302486
E. Hussein, N. Qasem, Maryam S. Jameel, Muhammad Ilyas, O. Bayat
This paper introduces a design of a single rectangular Microstrip Patch Antenna (MPA) with inset feed at frequency of 60 GHz using a Frequency Selective Surface (FSS). After implanting the FSS in the single MPA, it is found that some parameters have been improved. The selected geometry was the Square Loop (SL) element in FSS which has the best performance over other simple shapes. This paper aims to introduce an improvement of the parameter of a MPA, particularly, the gain, return loss, and bandwidth. These improvements has been investigated using Computer Simulation Technology (CST) Microwave Studio (MWS) simulator. The design is performed for 60 GHz applications. The 60 GHz band suffers from severe attenuation due to propagation. The oxygen absorption and the free-space path loss happen at 60 GHz are presumed in this study. These combined factors result in a poor link budget.
{"title":"Performance Optimization of Microstrip Patch Antenna Using Frequency Selective Surfaces for 60 GHz","authors":"E. Hussein, N. Qasem, Maryam S. Jameel, Muhammad Ilyas, O. Bayat","doi":"10.1109/SIU49456.2020.9302486","DOIUrl":"https://doi.org/10.1109/SIU49456.2020.9302486","url":null,"abstract":"This paper introduces a design of a single rectangular Microstrip Patch Antenna (MPA) with inset feed at frequency of 60 GHz using a Frequency Selective Surface (FSS). After implanting the FSS in the single MPA, it is found that some parameters have been improved. The selected geometry was the Square Loop (SL) element in FSS which has the best performance over other simple shapes. This paper aims to introduce an improvement of the parameter of a MPA, particularly, the gain, return loss, and bandwidth. These improvements has been investigated using Computer Simulation Technology (CST) Microwave Studio (MWS) simulator. The design is performed for 60 GHz applications. The 60 GHz band suffers from severe attenuation due to propagation. The oxygen absorption and the free-space path loss happen at 60 GHz are presumed in this study. These combined factors result in a poor link budget.","PeriodicalId":312627,"journal":{"name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123862937","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}
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