Proceedings of the 2nd International Conference on Control and Computer Vision最新文献

Research of the Time-dependent Electric Vehicle Routing Problem 时变电动汽车路径问题研究

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341033

Kaiji Liu, P. Ye, Tao Hong, Bo Li

引用次数: 2

Controlling Software Evolution Process Using Code Smell Visualization 利用代码气味可视化控制软件进化过程

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341026

Nabilah, W. Sunindyo

{"title":"Controlling Software Evolution Process Using Code Smell Visualization","authors":"Nabilah, W. Sunindyo","doi":"10.1145/3341016.3341026","DOIUrl":"https://doi.org/10.1145/3341016.3341026","url":null,"abstract":"Software change is inevitable, evolution becomes a part of software lifetime, and software release becomes more frequent. Hence there is a need for the project manager to inspect and control the process during software development and evolution. In the evolutionary stage, developers will face problems related to program code, one of that is identification of code smells. This problem could negatively affect maintainability in evolution, a developer needs more time and money. Visualization techniques turn data into a visual form so that it can provide information that is easier to understand. In software evolution, visualization mostly is used to view structure code. Previous research on evolution visualization limited to visualize the addition of code, the last update, release history, and information of developer that made the last change in program. However, this visualization is not enough to support understanding for the developers. We propose a visualization method for identifying code smell of the evolution software on java programming, so the developers can more easily understand the code that will be evolved. By knowing where the smell of code in the program, programmers can immediately do refactoring, the time and costs needed will also be low. Visualization of code smell is something new in the domain of software evolution. Finally, this design created to build tools in detecting code smells for software evolution process control.","PeriodicalId":278141,"journal":{"name":"Proceedings of the 2nd International Conference on Control and Computer Vision","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127458362","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: 3

Research on the Fast Image Motion Compensation Technology of Aerial Digital Camera 航空数码相机快速像移补偿技术研究

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341641

Chen Weining, Lei Yangjie, Yang Tao

引用次数: 1

Modified Watershed Transform for Automated Brain Segmentation from Magnetic Resonance Images 基于改进分水岭变换的脑磁共振图像自动分割

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341028

Siamak Roshanzadeh, Masoud Afrakhteh

{"title":"Modified Watershed Transform for Automated Brain Segmentation from Magnetic Resonance Images","authors":"Siamak Roshanzadeh, Masoud Afrakhteh","doi":"10.1145/3341016.3341028","DOIUrl":"https://doi.org/10.1145/3341016.3341028","url":null,"abstract":"The segmentation of human brain from Magnetic Resonance Image (MRI) is one of the most important parts of clinical diagnostic. Brains' anatomical structures can be visualized and measured through image segmentation. Especially, while clinical analysis of magnetic resonance images, accurate segmentation is a crucial task for precise subsequent analysis. Watershed transform is a widely used segmentation method in medical image analysis filed. Regarding MRI images, they always contain noise caused by different operating equipment and environmental situation. However, the performance of the watershed transform depends on converges of numerous local minima on the image. Wrong regional minima on the image cause a high rate of over-segmentation of the watershed transform method. To address this problem, in this paper we propose a modified watershed transform method to prevent over-segmentation using k-means clustering method. Our modified watershed transform utilizes the k-means clustering method for region classification to remove wrong regional minima on image and provides a guideline for watershed transform to prevent the over-segmentation problem. Experimental results on brain MRI images evaluations (Dice coefficient: 95.32%) demonstrate that the proposed method can substantially prevent the over-segmentation problem of conventional watershed transform method.","PeriodicalId":278141,"journal":{"name":"Proceedings of the 2nd International Conference on Control and Computer Vision","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123119965","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

An Approach to Real Time Parking Management using Computer Vision 基于计算机视觉的实时停车管理方法

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341025

Abhiram Natarajan, Keshav Bharat, Guru Rajesh Kaustubh, Sai Praveen P. N., Minal Moharir, N. Srinath, K. Subramanya

{"title":"An Approach to Real Time Parking Management using Computer Vision","authors":"Abhiram Natarajan, Keshav Bharat, Guru Rajesh Kaustubh, Sai Praveen P. N., Minal Moharir, N. Srinath, K. Subramanya","doi":"10.1145/3341016.3341025","DOIUrl":"https://doi.org/10.1145/3341016.3341025","url":null,"abstract":"Automating vehicle statistics provides vital information that can be used in predicting the flow of traffic. Object detection based systems that use computer vision have produced drastic improvements in results over a sensor based approach. The methodology proposed in the paper follows an approach to perform this operation in real time and is currently being used in estimating the density of parking spaces, amongst other applications. The paper describes a 4 layer architecture for parking management which involves a HAAR based frame extraction from live video feed followed by a YOLOv2(You Only Look Once) deep neural network approach that supports real time detection of vehicles. The third layer emphasizes on the use of a mechanism that measures the number of vehicles entering a parking space by following the path traced by the centroid which is followed by a number plate recognition system that can retrace mishappenings to their source. The detection system developed using this model has been extensively tested on real time traffic in Bangalore and has generated accuracies close to 95% with video data that has been cross verified manually, making it much more effective than sensor based models.","PeriodicalId":278141,"journal":{"name":"Proceedings of the 2nd International Conference on Control and Computer Vision","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122634654","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: 3

Low Complexity Hybrid Beamforming for MmWave-UAV Communication Systems with a Pre-defined Codebook 具有预定义码本的毫米波-无人机通信系统的低复杂度混合波束形成

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341036

Quan Yu, Chao Han, Jingchao Wang, Lin Bai

{"title":"Low Complexity Hybrid Beamforming for MmWave-UAV Communication Systems with a Pre-defined Codebook","authors":"Quan Yu, Chao Han, Jingchao Wang, Lin Bai","doi":"10.1145/3341016.3341036","DOIUrl":"https://doi.org/10.1145/3341016.3341036","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) have been regarded as a candidate for future networks with high capacity requirement. However, the high mobility and agility of UAVs make the designation of the cooperative communication system more complex than that of the traditional terrestrial cell network, how to construct an aerial network efficiently for terrestrial terminals or users is still a hot spot. In this paper, we investigate the UAV-based wireless communication system where the detection performance for each user needs to be guaranteed. We mainly focus on two different types of communication systems, in the first kind of systems, the UAVs will hover above the targeted cell to communicate with different users simultaneously. A low complexity hybrid beamforming method for the UAV with finite resolution phase shifters (PSs) is proposed. Moreover, for the second type of UAV-based systems, the UAV can communicate with different user groups where only one user in a group could be motivated during a transmission block. We then propose an effective multiuser selection scheme to improve the efficiency of the system. Finally, from the simulation, we can confirm that the proposed methods are reasonable and attractive to the UAV-based communication system.","PeriodicalId":278141,"journal":{"name":"Proceedings of the 2nd International Conference on Control and Computer Vision","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124234161","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

An Efficient Method of PCB Images Stitching 一种高效的PCB图像拼接方法

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341032

Min Qi, Yingbo Wang, Yuelei Xu, Zhuang Li

引用次数: 1

A Robust and Effective Tracking Method in Remote Sensing Video Sequences 一种鲁棒有效的遥感视频序列跟踪方法

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341022

Bi Fukun, Lei Mingyang, Sun Jiayi

{"title":"A Robust and Effective Tracking Method in Remote Sensing Video Sequences","authors":"Bi Fukun, Lei Mingyang, Sun Jiayi","doi":"10.1145/3341016.3341022","DOIUrl":"https://doi.org/10.1145/3341016.3341022","url":null,"abstract":"With the popularization of high resolution imaging technology and the progress of artificial intelligence, remote sensing target tracking in the aerial video plays a very important role in public security, such as antiterrorism efforts and military reconnaissance. As aerial video has rapid changes in orientations, low resolution, and multiple similar disruptors, and the main tracking methods generally have relatively low tracking performance in this research field, we develop a robust tracking method for remote sensing videos based on a saliency enhanced multi-domain convolutional neural network (SEMD). The process can be divided into two main stages: (1) in the offline pretraining stage, we combine the Least Squares Generative Adversarial Networks (LSGANs) with a rotation strategy to augment typical easily confused negative samples, which can improve the capacity to distinguish between target and the background. (2) in the online tracking process, a saliency module is embedded between convolutional layers and we optimize the arrangement of its functional sub-modules to boost the saliency of the feature map, which improve the network representation power for rapid dynamic changes in the target. Comprehensive evaluations of homemade datasets demonstrate that the proposed method can achieve high efficiency and accuracy results compared to state-of-the-art methods.","PeriodicalId":278141,"journal":{"name":"Proceedings of the 2nd International Conference on Control and Computer Vision","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131539788","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

Cyber Governance Complex in Firms 企业的网络治理综合体

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341037

M. Kikuchi, T. Okubo

引用次数: 4

Design of Vibration Monitoring System and Its Application in Grape Fatigue Damage Research 振动监测系统的设计及其在葡萄疲劳损伤研究中的应用

Proceedings of the 2nd International Conference on Control and Computer Vision Pub Date : 2019-06-15 DOI: 10.1145/3341016.3341041

Xiaoqing Hu, Yan Xu, Jun Liu

引用次数: 2