2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)最新文献_第3页

Comparison of DC Motor Position Control Simulation using MABSA-FLC and PSO-FLC 基于MABSA-FLC和PSO-FLC的直流电机位置控制仿真比较

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-03 DOI: 10.1109/CSPA.2019.8696032

N. Elias, N. M. Yahya

引用次数: 1

Review on Current Methods of Gait Analysis and Recognition using Kinect 基于Kinect的步态分析与识别方法综述

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8695979

R. Sahak, N. K. Zakaria, N. Tahir, A. Yassin, R. Jailani

引用次数: 4

Super Resolution of Car Plate Images Using Generative Adversarial Networks 基于生成对抗网络的超分辨率车牌图像

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8696010

Tan Kean Lai, A. F. Abbas, A. M. Abdu, U. U. Sheikh, M. Mokji, K. Khalil

{"title":"Super Resolution of Car Plate Images Using Generative Adversarial Networks","authors":"Tan Kean Lai, A. F. Abbas, A. M. Abdu, U. U. Sheikh, M. Mokji, K. Khalil","doi":"10.1109/CSPA.2019.8696010","DOIUrl":"https://doi.org/10.1109/CSPA.2019.8696010","url":null,"abstract":"Car plate recognition is used in traffic monitoring and control systems such as intelligent parking lot management, finding stolen vehicles, and automated highway toll. In practice, Low-Resolution (LR) images or videos are widely used in surveillance systems. In low resolution surveillance systems, the car plate text is often illegible. Super-Resolution (SR) techniques can be used to improve the car plate quality by processing a series of LR images into a single High-Resolution (HR) image. Recovering the HR image from a single LR is still an ill-conditioned problem for SR. Previous methods always minimize the mean square loss in order to improve the peak signal to noise ratio (PSNR). However, minimizing the mean square loss leads to overly smoothed reconstructed image. In this paper, Generative Adversarial Networks (GANs) based SR is proposed to reconstruct the LR images into HR images. Besides that, perceptual loss is proposed to solve the smoothing issue. The quality of the GAN based SR generated images is compared to existing techniques such as bicubic, nearest and Super-Resolution Convolution Neural Network (SRCNN). The results show that the reconstructed images using GANs based SR achieve better results in term of perceptual quality compared to previous methods.","PeriodicalId":400983,"journal":{"name":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126940328","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: 6

Light Database Encryption Design Utilizing Multicore Processors for Mobile Devices 基于多核处理器的移动设备轻数据库加密设计

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8696084

M. Alomari, M. Hafiz Yusoff, K. Samsudin, R. Ahmad

{"title":"Light Database Encryption Design Utilizing Multicore Processors for Mobile Devices","authors":"M. Alomari, M. Hafiz Yusoff, K. Samsudin, R. Ahmad","doi":"10.1109/CSPA.2019.8696084","DOIUrl":"https://doi.org/10.1109/CSPA.2019.8696084","url":null,"abstract":"The confidentiality of data stored in embedded and handheld devices has become an urgent necessity more than ever before. Encryption of sensitive data is a well-known technique to preserve their confidentiality, however it comes with certain costs that can heavily impact the device processing resources. Utilizing multicore processors, which are equipped with current embedded devices, has brought a new era to enhance data confidentiality while maintaining suitable device performance. Encrypting the complete storage area, also known as Full Disk Encryption (FDE) can still be challenging, especially with newly emerging massive storage systems. Alternatively, since the most user sensitive data are residing inside persisting databases, it will be more efficient to focus on securing SQLite databases, through encryption, where SQLite is the most common RDBMS in handheld and embedded systems. This paper addresses the problem of ensuring data protection in embedded and mobile devices while maintaining suitable device performance by mitigating the impact of encryption. We presented here a proposed design for a parallel database encryption system, called SQLite-XTS. The proposed system encrypts data stored in databases transparently on-the-fly without the need for any user intervention. To maintain a proper device performance, the system takes advantage of the commodity multicore processors available with most embedded and mobile devices.","PeriodicalId":400983,"journal":{"name":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130232870","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

Fire Fighter Robot with Night Vision Camera 配备夜视摄像头的消防机器人

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8696077

K. Perumal, Musab A. M. Ali, Zainab Hussein Yahya

引用次数: 11

Relationship of Environmental Factors Toward Accident Cases using GIS Application in Kedah GIS应用于吉打州环境因素与事故的关系

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8695972

Nur Fatma Fadilah Yaacob, N. Rusli, S. N. Bohari

{"title":"Relationship of Environmental Factors Toward Accident Cases using GIS Application in Kedah","authors":"Nur Fatma Fadilah Yaacob, N. Rusli, S. N. Bohari","doi":"10.1109/CSPA.2019.8695972","DOIUrl":"https://doi.org/10.1109/CSPA.2019.8695972","url":null,"abstract":"Malaysia has been ranked as one of the top three countries in the world with deadliest roads. The aim of this study is to determine the relationship between environmental factors and the occurrence of accident cases. The road accident data were obtained from Ibu Pejabat Kontinjen (IPK) Alor Setar and the weather data were obtained from the Malaysian Meteorological Department (MMD) from the year 2013 to 2015. These data were processed through ArcGIS software 10.5. Subsequently, to determine the relationship between accident cases and environmental factors, the regression method was carried out. The result show rainfall has effects toward road accidents at the low level of rainfall. Besides that, there are two levels of temperature that lead to accidents occurring in Kedah such as cool day and warm day. The number of accident cases increased when the temperature value in cool day category increased and the number of road accident cases occurred decreased when the temperature value increased in warm day category. Meanwhile, the number of accident cases increased when the wind speed is maximum or above 20 m/s. In conclusion, the advancements in Geographical Information System (GIS) can be put to effective use in road accidents for further analysis such as spatial-temporal analysis, hotspots area analysis, shortest path analysis and emergency response analysis.","PeriodicalId":400983,"journal":{"name":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126031680","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

Tailoring OTHR Deployment in Order to Meet Conditions in Remote Equatorial Areas 调整其他武器部署，以满足偏远赤道地区的条件

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8696093

D. Nikolić, N. Tosic, Bojan Džolić, Nemanja Grbić, Pavle Z. Petrović, Ana I. Djurdjevic, Nikola Lekić

引用次数: 6

Automatic Disease Symptoms Segmentation Optimized for Dissimilarity Feature Extraction in Digital Photographs of Plant Leaves 植物叶片数字照片中不同特征提取的疾病症状自动分割优化

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8696049

A. M. Abdu, Musa Mohd Mokji, U. U. Sheikh, K. Khalil

{"title":"Automatic Disease Symptoms Segmentation Optimized for Dissimilarity Feature Extraction in Digital Photographs of Plant Leaves","authors":"A. M. Abdu, Musa Mohd Mokji, U. U. Sheikh, K. Khalil","doi":"10.1109/CSPA.2019.8696049","DOIUrl":"https://doi.org/10.1109/CSPA.2019.8696049","url":null,"abstract":"Segmentation of diseased symptom regions in images of plant leaves is a crucial stage in the application of machine learning for plant diseases detection. This process also known as Region of Interest (ROI) segmentation involves separating purely color variant symptom lesions from surrounding green tissue from which discriminant features are later extracted. However, investigations have shown that vivid anatomy of a disease symptom progression right from inception to manifestation through which finer disease characterization dissimilarity features can be fostered are not captured in a segmented ROI. Furthermore, the typical ROI segmentation process is often plagued by challenges ranging from intrinsic factors such as image capture conditions to extrinsic factors such as disease anatomy where symptoms fade into healthy green tissue the separation boundary to become impalpable. This adds further complexity to the process or produce erroneous result. This research proposes an automatic extended region of interest (EROI) segmentation to incorporate symptom progression information by extending the border region to cover some part of healthy tissue using color homogeneity thresholding. To produce a ground truth, the typical ROI segmentation alongside a reduced ROI were implemented on a well-known PlantVillage dataset from which separate textural and color features were extracted and used to build a linear classifier. A comparison between the classification results further reinforced the advantages of the proposed approach for dissimilarity features extraction. Through this research, finer characterization features can be extracted for the classification and severity estimation of plant diseases.","PeriodicalId":400983,"journal":{"name":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123220152","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: 10

An Improved Deep Neural Network for Classification of Plant Seedling Images 植物幼苗图像分类的改进深度神经网络

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/CSPA.2019.8696009

Catherine R. Alimboyong, Alexander A. Hernandez

{"title":"An Improved Deep Neural Network for Classification of Plant Seedling Images","authors":"Catherine R. Alimboyong, Alexander A. Hernandez","doi":"10.1109/CSPA.2019.8696009","DOIUrl":"https://doi.org/10.1109/CSPA.2019.8696009","url":null,"abstract":"This scientific pursuit aimed to develop a deep learning architecture tailored to classify plant seedling images. Our architecture encompasses seven learned layers - five convolutions and two fully connected. We performed full training on the network using 4, 234 plant seedling images belonging to twelve plant species from Aarhus University Signal Processing group. The system is fine-tuned for the architecture to have greater processing time and low memory consumption. The architecture was evaluated using different network parameters. Furthermore, we used training loss function, accuracy, sensitivity, and specificity to evaluate the system performance. Experimental results proved that the developed architecture has reached excellent performance with overall accuracy of 90.15%. Results were achieved in 111 minutes and 36 seconds. Future work includes, first, use the model with greater amount of datasets through data augmentation and compare the results to other existing deep learning architectures using same datasets. Second, authors will consider CNN and RNN architectures together using several other plant datasets. Third, create a portable mobile application for plant seedling images classification utilizing the developed model.","PeriodicalId":400983,"journal":{"name":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123352184","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: 15

2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA) Pub Date : 2019-03-01 DOI: 10.1109/cspa.2019.8695977

引用次数: 0