2021 Systems and Information Engineering Design Symposium (SIEDS)最新文献_第4页

Enemy Location Prediction in Naval Combat Using Deep Learning 基于深度学习的海战敌人位置预测

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483759

Morgan Freiberg, Kent McLaughlin, A. Ningtyas, Oliver Taylor, Stephen Adams, P. Beling, Roy Hayes

{"title":"Enemy Location Prediction in Naval Combat Using Deep Learning","authors":"Morgan Freiberg, Kent McLaughlin, A. Ningtyas, Oliver Taylor, Stephen Adams, P. Beling, Roy Hayes","doi":"10.1109/SIEDS52267.2021.9483759","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483759","url":null,"abstract":"The immensely complex realm of naval warfare presents challenges for which machine learning is uniquely suited. In this paper, we present a machine learning model to predict the location of unseen enemy ships in real time, based on the current known positions of other ships on the battlefield. More broadly, this research seeks to validate the ability of basic machine learning algorithms to make meaningful classifications and predictions of simulated adversarial naval behavior. Using gameplay data from World of Warships, we deployed an artificial neural network (ANN) model and a Random Forest model to serve as prediction engines that update as the battle progresses, overlaying probabilities over the battlefield map indicating the likelihood of the unseen ship being at each location. The models were trained and tested on gameplay data from a World of Warships tournament in which former naval officers served as commanders of competing fleets. This tournament structure ensured cohesive and coordinated naval fleet behavior, yielding data similar to that seen in real-world naval combat and increasing the applicability of our model. Both the Random Forest and ANN model were successful in their predictive capabilities, with the ANN proving to be the best method.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133035108","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

Developing Models to Predict Giving Behavior of Nonprofit Donors 开发模型来预测非营利捐赠者的捐赠行为

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483771

Josh Eiland, Clare Hammonds, Sofia M. Ponos, Shawn M. Weigand, W. Scherer

{"title":"Developing Models to Predict Giving Behavior of Nonprofit Donors","authors":"Josh Eiland, Clare Hammonds, Sofia M. Ponos, Shawn M. Weigand, W. Scherer","doi":"10.1109/SIEDS52267.2021.9483771","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483771","url":null,"abstract":"Organizations in the nonprofit space are increasingly using data mining techniques to gain insights into their donors’ behaviors and motivations. Data mining can be costly but can also be valuable in retaining and obtaining donors. Throughout the course of this project, we have prioritized two objectives. One is to increase the ratio of funds raised to dollars spent on fundraising from current donors, making these efforts more profitable. The other is to determine how to most effectively solicit new donors. To accomplish these goals, we have used statistical modeling and data analysis to gain insights and create recommendations related to donor optimization and acquisition. To learn about the current donors, it is important to identify which unique traits make donors more likely to donate and whether those traits are related to an individual’s demographic information or giving history. Our team is classifying donors into \"states\" of giving based upon different metrics, including how recently, how much, how often, and for how long they have donated. We are using various data models to create actionable recommendations on how to tailor fundraising appeals specifically to different donors, which will increase the Inn’s overall donations and their return on fundraising investment. We are also mapping the transitions between these giving states so that donors dropping from higher states can be re-engaged, while donors with a high chance of moving into a more profitable state can be flagged and targeted. We will present these results in a dashboard that the Inn can use moving forward to better solicit each donor and maintain a steady fundraising revenue stream.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114568607","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

Managing Cybersecurity Risk Using Threat Based Methodology for Evaluation of Cybersecurity Architectures 使用基于威胁的方法对网络安全架构进行评估来管理网络安全风险

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483736

Branko Bokan, Joost Santos

{"title":"Managing Cybersecurity Risk Using Threat Based Methodology for Evaluation of Cybersecurity Architectures","authors":"Branko Bokan, Joost Santos","doi":"10.1109/SIEDS52267.2021.9483736","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483736","url":null,"abstract":"To manage limited resources available to protect against cybersecurity threats, organizations must use risk management approach to prioritize investments in protection capabilities. Currently, there is no commonly accepted methodology for cybersecurity professionals that considers one of the key elements of risk function – threat landscape – to identify gaps (blinds spots) where cybersecurity protections do not exist and where future investments are needed. This paper discusses a new, threat-based approach for evaluation of cybersecurity architectures that allows organizations to look at their cybersecurity protections from the standpoint of an adversary. The approach is based on a methodology developed by the Department of Defense and further expanded by the Department of Homeland Security. The threat-based approach uses a cyber threat framework to enumerate all threat actions previously observed in the wild and scores protections (cybersecurity architectural capabilities) against each threat action for their ability to: a) detect; b) protect against; and c) help in recovery from the threat action. The answers form a matrix called capability coverage map – a visual representation of protections coverage, gaps, and overlaps against threats. To allow for prioritization, threat actions can be organized in a threat heat map – a visual representation of threat actions’ prevalence and maneuverability that can be overlaid on top of a coverage map. The paper demonstrates a new threat modeling methodology and recommends future research to establish a decision-making framework for designing cybersecurity architectures (capability portfolios) that maximize protections (described as coverage in terms of protect, detect, and respond functions) against known cybersecurity threats.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121923746","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

Developing a Dashboard for High Occupancy Buildings 开发用于高占用率建筑的仪表板

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483791

C. Berger, Kayleigh Calder, Sarah M. Cassway, Caroline Walton

{"title":"Developing a Dashboard for High Occupancy Buildings","authors":"C. Berger, Kayleigh Calder, Sarah M. Cassway, Caroline Walton","doi":"10.1109/SIEDS52267.2021.9483791","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483791","url":null,"abstract":"Energy management tools have become essential for high occupancy buildings because they allow building managers to understand their building’s energy efficiency and identify areas of environmental waste. However, a published and customizable energy management tool standardized for all high occupancy buildings currently does not exist, requiring individual companies to spend time and money creating one that more accurately models their building’s energy efficiency. In this project, we developed the prototype Dean Dashboard, a customizable energy management tool that analyzes a building’s energy usage and optimizes the cost to meet a goal of obtaining the Leadership in Energy and Environmental Design (LEED) Operation and Maintenance (O&M) certification. This project uses an M.C. Dean operated-and-maintained facility as the case model. M.C. Dean is a design-build company for mission-critical facilities. The Dean Dashboard is comprised of five key features: exponentially weighted moving average (EWMA) forecasting models, EWMA control charts, energy efficiency metric calculations, a LEED score optimization model, and a system improvement analysis. Through the integration of these features, the dashboard provides detailed insights into a building’s energy consumption and provides recommendations for how the building can improve its energy efficiency.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123470814","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 Text Analysis of the 2020 U.S. Presidential Election Campaign Speeches 2020年美国总统竞选演讲文本分析

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483735

Kevin Finity, Ramit Garg, Max McGaw

{"title":"A Text Analysis of the 2020 U.S. Presidential Election Campaign Speeches","authors":"Kevin Finity, Ramit Garg, Max McGaw","doi":"10.1109/SIEDS52267.2021.9483735","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483735","url":null,"abstract":"Campaign speeches provide significant insight into how candidates communicate their message and highlight their priorities to various audiences. This study explores the campaign speeches of Donald Trump, Joseph Biden, Michael Pence, and Kamala Harris during the 2020 US presidential election using Natural Language Processing (NLP) techniques and a novel data pipeline of unstructured automated video captions. The intent of this effort is to evaluate the stylistic elements of the candidate speeches through elements such as formality, repetitiveness, topic variance, sentiment, and vocabulary choice/range to establish how candidates differ in their approaches and what effectively resonates with the voters. The NLP methods used include unsupervised similarity and clustering algorithms. Through this work, the results uncovered large stylistic differences amongst the candidates overall; however, more notably also indicate stark differences between the top and bottom of the Republican ticket compared to the Democratic ticket. The findings support the idea that the candidate pairs were selected strategically to cover the largest bloc of voters possible as part of the election process.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125558957","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

Data Analytics for Cyber Risk Analysis Utilizing Cyber Incident Datasets 利用网络事件数据集进行网络风险分析的数据分析

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483743

Melissa Portalatin, O. Keskin, Sneha Malneedi, Owais Raza, Unal Tatar

{"title":"Data Analytics for Cyber Risk Analysis Utilizing Cyber Incident Datasets","authors":"Melissa Portalatin, O. Keskin, Sneha Malneedi, Owais Raza, Unal Tatar","doi":"10.1109/SIEDS52267.2021.9483743","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483743","url":null,"abstract":"The imperative factors of cybersecurity within institutions have become prevalent due to the rise of cyber-attacks. Cybercriminals strategically choose their targets and develop several different techniques and tactics that are used to exploit vulnerabilities throughout an entire institution. With the thorough analysis practices being used in recent policy and regulation of cyber incident reports, it has been claimed that data breaches have increased at alarming rates rapidly. Thus, capturing the trends of cyber-attacks strategies, exploited vulnerabilities, and reoccurring patterns as insight to better cybersecurity. This paper seeks to discover the possible threats that influence the relationship between the human component and cybersecurity posture. Along with this, we use the Vocabulary for Event Recording and Incident Sharing (VERIS) database to analyze previous cyber incidents to advance risk management that will benefit the institutional level of cybersecurity. We elaborate on the rising concerns of external versus internal factors that potentially put institutions at risk for exploiting vulnerabilities and conducting an exploratory data analysis that articulates the understanding of detrimental monetary and data loss in recent cyber incidents. The human component of this research attributes to the perceptive of the most common cause within cyber incidents, human error. With these concerns on the rise, we found contributing factors with the use of a risk-based approach and thorough analysis of databases, which will be used to improve the practical consensus of cybersecurity. Our findings can be of use to all institutions in search of useful insight to better their risk-management planning skills and failing elements of their cybersecurity.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125621448","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

Investigating Novel Proximity Monitoring Techniques Using Ubiquitous Sensor Technology 利用泛在传感器技术研究新型接近监测技术

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483795

Seanna Adam, B. Coward, Grayson DeBerry, Caroline Glazier, Evan Magnusson, M. Boukhechba

{"title":"Investigating Novel Proximity Monitoring Techniques Using Ubiquitous Sensor Technology","authors":"Seanna Adam, B. Coward, Grayson DeBerry, Caroline Glazier, Evan Magnusson, M. Boukhechba","doi":"10.1109/SIEDS52267.2021.9483795","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483795","url":null,"abstract":"The goal of this work is to investigate novel proximity detection techniques by researching and testing various sensor technologies and investigate their feasibility in an athletic context. COVID-19 has challenged sports teams to come up with reasonable and easy-to-implement solutions to provide a safe training environment for their players and staff. For this reason, proximity data is more important than ever, as many teams are in need of a way to measure social distancing and maintain contact tracing of their athletes. Bluetooth has been widely used to detect colocation and monitor social distancing. However, there are many other sensing technologies that may prove to be more accurate, robust, and secure. Therefore, the focus of this work is to investigate how Bluetooth compares with ultra-wideband and ultrasound technologies when monitoring the distance between users. We have implemented and compared the three modalities in a controlled experiment to investigate their accuracy at detecting distance between users at various levels. Our results indicate that the UWB signals are the most accurate at monitoring co-location.This is in-line with previous research suggesting that Bluetooth cannot accurately measure the distance between fast moving objects and needs about 20 seconds to stabilize distance measurements; therefore, it is not feasible to use for sports. In addition, we recorded that UWB models yielded an accuracy of over 95%, while ultrasound correctly classified the observations over 80% of the time, and Bluetooth had an accuracy of less than 50% when predicting if a given signal is within 6 feet or not.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117210837","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

Towards Automating Search and Classification of Protostellar Images 原恒星图像的自动搜索与分类

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483748

Pavan Kumar Bondalapati, Pengwei Hu, Shannon E Paylor, John Zhang

{"title":"Towards Automating Search and Classification of Protostellar Images","authors":"Pavan Kumar Bondalapati, Pengwei Hu, Shannon E Paylor, John Zhang","doi":"10.1109/SIEDS52267.2021.9483748","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483748","url":null,"abstract":"Research on the origins of planets and life centers around protoplanetary disks and protostars, for which the Atacama Large Millimeter/sub-millimeter Array (ALMA) has been revolutionary due to its ability to capture high-resolution images with exceptional sensitivity. Astronomers study these birthplaces of planets and their properties, which determine the properties of any eventual planets. The ALMA science archive contains over a petabyte of astronomical data which has been collected by the ALMA telescope over the last decade. While the archive data is publicly available, manually searching through many thousands of unlabelled images and ascertaining the type and physical properties of celestial objects is immensely labor-intensive. For these reasons, an exhaustive manual search of the archive is unlikely to be comprehensive and creates the potential for astronomers to miss objects that were not the primary target of the telescope observational program. We develop a Python package to automate the noise filtration process, identify astronomical objects within a single image, and fit bivariate Gaussians to each detection. We apply an unsupervised learning algorithm to identify many apparently different protostellar disk images in a curated ALMA data set. Using this model and the residuals from a bivariate Gaussian fit, we can flag images of an unusual nature (e.g. spiral, ring, or other structure that does not adhere to a bivariate Gaussian shape) for manual review by astronomers, allowing them to examine a small subset of interesting images without sifting through the entire archive. Our open-source package is intended to assist astronomers in making new scientific discoveries by eliminating a labor-intensive bottleneck in their research.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121222171","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

Behind the Meter: Implementing Distributed Energy Technologies to Balance Energy Load in Virginia 电表后面:在弗吉尼亚州实施分布式能源技术以平衡能源负荷

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483710

T. Anderson, Daniel Collins, Chloé Fauvel, Harrison Hurst, Nina Mellin, Bailey Thran, A. Clarens, Arthur Small

{"title":"Behind the Meter: Implementing Distributed Energy Technologies to Balance Energy Load in Virginia","authors":"T. Anderson, Daniel Collins, Chloé Fauvel, Harrison Hurst, Nina Mellin, Bailey Thran, A. Clarens, Arthur Small","doi":"10.1109/SIEDS52267.2021.9483710","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483710","url":null,"abstract":"One of the principal challenges associated with decarbonization is the temporal variability of renewable energy generation, which is creating the need to better balance load on the grid by shaving peak demand. We analyzed how innovative load-shifting technologies can be used by large institutions like the University of Virginia to shift load and support statewide efforts to decarbonize. To do this, we focused on the University's plans for expansion of the Fontaine Research Park, which is a good model for understanding how these technologies could distribute energy load behind the meter. First, we worked to develop a predictive model to forecast when peak demands will occur and understand how interventions, including heat recovery chillers and thermal storage tanks, might be used to balance load. Then, we extended a statewide energy systems model using the Tools for Energy Modeling Optimization and Analysis (TEMOA) to simulate the ways in which these types of interventions might be scaled to the whole state. Using the energy demand model in conjunction with aggregated institutional energy use data, the team evaluated the effects that broader adoption of distributed energy technologies in Virginia could have on the grid's ability to handle the energy transition. Our study showed implementing distributed energy sources on a state-scale had insignificant effect on balancing load. However, on a microgrid scale, such technologies prove to be a useful resource to decrease peak demand which would allow for further clean energy projects and possible cost reductions.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122391547","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 Robust Pedestrian and Cyclist Detection Method Using Thermal Images 一种基于热图像的鲁棒行人和自行车检测方法

2021 Systems and Information Engineering Design Symposium (SIEDS) Pub Date : 2021-04-30 DOI: 10.1109/SIEDS52267.2021.9483730

Navya Annapareddy, E. Sahin, Sander Abraham, Md. Mofijul Islam, M. Depiro, T. Iqbal

{"title":"A Robust Pedestrian and Cyclist Detection Method Using Thermal Images","authors":"Navya Annapareddy, E. Sahin, Sander Abraham, Md. Mofijul Islam, M. Depiro, T. Iqbal","doi":"10.1109/SIEDS52267.2021.9483730","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483730","url":null,"abstract":"Computer vision techniques have been frequently applied to pedestrian and cyclist detection for the purpose of providing sensing capabilities to autonomous vehicles, and delivery robots among other use cases. Most current computer vision approaches for pedestrian and cyclist detection utilize RGB data alone. However, RGB-only systems struggle in poor lighting and weather conditions, such as at night, or during fog or precipitation, often present in pedestrian detection contexts. Thermal imaging presents a solution to these challenges as its quality is independent of time of day and lighting conditions. The use of thermal imaging input, such as those in the Long Wave Infrared (LWIR) range, is thus beneficial in computer vision models as it allows the detection of pedestrians and cyclists in variable illumination conditions that would pose challenges for RGB-only detection systems. In this paper, we present a pedestrian and cyclist detection method via thermal imaging using a deep neural network architecture. We have evaluated our proposed method by applying it to the KAIST Pedestrian Benchmark dataset, a multispectral dataset with paired RGB and thermal images of pedestrians and cyclists. The results suggest that our method achieved an F1-score of 81.34%, indicating that our proposed approach can successfully detect pedestrians and cyclists from thermal images alone.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123191382","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