发布求助
文献互助 智能选刊 最新文献

2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)最新文献

筛选
英文 中文
Distance estimation using mono camera at different altitudes and pitch angles 用单摄像机在不同高度和俯仰角下进行距离估计
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378676
Nurgeldy Praliyev, Viktor Remeli, Z. Szalay
{"title":"Distance estimation using mono camera at different altitudes and pitch angles","authors":"Nurgeldy Praliyev, Viktor Remeli, Z. Szalay","doi":"10.1109/SAMI50585.2021.9378676","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378676","url":null,"abstract":"This article presents two prospective methods for vehicle distance estimation utilizing a single camera at different altitudes and camera pitch angles. A distance estimation procedure was conducted applying real-life visualization and homography approaches. Experimental outputs showed that the real-life visualization method overperforms the homography at all altitudes and distance ranges. The performance of the homography can be improved by locating the camera at higher locations with more pronounced tilt angles as it would provide less error / pixel at the cost of a reduced field of view. Overall, both introduced techniques perform better at higher camera positions and closer target distances. Application of mentioned methods in vehicles is a simple and economical way to improve their autonomy and reduce road risk level.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122121461","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
Data engineering case-study in digitalized manufacturing 数字化制造中的数据工程案例研究
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378691
István Pölöskei
{"title":"Data engineering case-study in digitalized manufacturing","authors":"István Pölöskei","doi":"10.1109/SAMI50585.2021.9378691","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378691","url":null,"abstract":"The combination of big data and machine learning appears in the manufacturing context frequently. In a modern factory, data is collected everywhere. It is a challenge for the companies, finding their way to use the produced data. The model's quality is strongly dependent on the quality of the training dataset; the data engineer is responsible for the infrastructure, like providing context and quality input-data for machine learning algorithms. In the discussed case-study, a data pipeline is introduced as a potential solution. It proposes a strategy through the organization, from the shop floor to decision- makers.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121551667","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
Text Classifications Learned from Language Model Hidden Layers 基于语言模型隐藏层的文本分类
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378669
Nathaniel R. Robinson, Zachary Brown, Timothy Sitze, Nancy Fulda
{"title":"Text Classifications Learned from Language Model Hidden Layers","authors":"Nathaniel R. Robinson, Zachary Brown, Timothy Sitze, Nancy Fulda","doi":"10.1109/SAMI50585.2021.9378669","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378669","url":null,"abstract":"Advancements in machine learning methods have yielded powerful natural language generation models. However, in general, these models have drawn concern for being both uninterpretable and uncontrollable. Model interpretability and control have become important topics of interest among researchers. We explore a variety of machine learning methods to classify the hidden states of language models. This classification enables model interpretation at a deep semantic level and is a necessary part of recently proposed model control methods. We show further that the use of language model hidden layers as text representations in classification tasks may be more reliable in some applications than more standard text representations.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130253548","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
Algorithm for on-line calendar text generation in public transport 公共交通在线日历文本生成算法
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378616
Jaromír Šulc, Kateřina Šulcová
{"title":"Algorithm for on-line calendar text generation in public transport","authors":"Jaromír Šulc, Kateřina Šulcová","doi":"10.1109/SAMI50585.2021.9378616","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378616","url":null,"abstract":"This article describes heuristic algorithm generating calendar text for various stop timetables and for usage of third parties, i. e. governments, companies, vehicle computers, clearing centers etc. For convenience and better user experience, the calendar text does not usually contain simple list of days, but rather variations of shorter and more meaningful texts relevant to human understanding of time intervals. The goal of the algorithm is on-line distribution of trips into all published symbols (for example the pair of symbols: workdays, weekends), and conversion of differences between trips validity and each symbol validity into a short readable text. The algorithm is using standard and user defined symbols. For the given published symbol, we find for each trip the minimal number of subintervals with similar pattern. For each subinterval, we generate calendar text with positive and negative meaning and we publish the shorter one. The algorithm was developed and tested on timetables data of several Czech cities, and currently is implemented within a software for timetabling and within several public information systems of Czech transport companies.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127061657","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
Measurement of Water Consumption based on Image Processing 基于图像处理的用水量测量
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378611
O. Kainz, Matus Dujava, R. Petija, M. Michalko, F. Jakab
{"title":"Measurement of Water Consumption based on Image Processing","authors":"O. Kainz, Matus Dujava, R. Petija, M. Michalko, F. Jakab","doi":"10.1109/SAMI50585.2021.9378611","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378611","url":null,"abstract":"The aim of this paper is the proposal of the solution for automated visual collection of water consumption data and subsequent processing of extracted data in order to detect non-standard situations. Proposed solution is capable of detecting all types of water leakage occurring after the installed water consumption meter, providing the water meter is not digital.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125257486","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
Welcome from the Chairs 欢迎大家
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/sami50585.2021.9378609
Vadim Zaytsev, Jesús M. González-Barahona, Barbara Paech, Kaj Dreef, James Jones, Michael Philippsen, Samuel Beck, Sebastian Frank, M. A. Hakamian, Leonel, Merino, A. Hoorn, A. Dery, Patric Genfer, Eray Tüzün, Alberto Bacchelli, Mircea Lungu, Wilhelm Hasselbring, Otto Seppälä
{"title":"Welcome from the Chairs","authors":"Vadim Zaytsev, Jesús M. González-Barahona, Barbara Paech, Kaj Dreef, James Jones, Michael Philippsen, Samuel Beck, Sebastian Frank, M. A. Hakamian, Leonel, Merino, A. Hoorn, A. Dery, Patric Genfer, Eray Tüzün, Alberto Bacchelli, Mircea Lungu, Wilhelm Hasselbring, Otto Seppälä","doi":"10.1109/sami50585.2021.9378609","DOIUrl":"https://doi.org/10.1109/sami50585.2021.9378609","url":null,"abstract":"Computational Intelligence and Intelligent Technologies are very important tools in building intelligent systems with various degree of autonomous behavior. These groups of tools support such features as ability to learn and adaptability of the intelligent systems in various types of environments and situations. The current and future Information Society is expecting to be implemented with the framework of the Ambient Intelligence (AmI) approach into technologies and everyday life. These accomplishments provide the wide range of application potentials for Machine Intelligence tools to support the AmI concept implementation. The number of studies indicates that this approach is inevitable and will play essential and central role in the development of Information Society in close future.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123779881","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
Psychophysiological modelling of trust in technology: Comparative analysis of algorithm ensemble methods 技术信任的心理生理模型:算法集成方法的比较分析
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378655
I. B. Ajenaghughrure, Sònia Cláudia Da Costa Sousa, D. Lamas
{"title":"Psychophysiological modelling of trust in technology: Comparative analysis of algorithm ensemble methods","authors":"I. B. Ajenaghughrure, Sònia Cláudia Da Costa Sousa, D. Lamas","doi":"10.1109/SAMI50585.2021.9378655","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378655","url":null,"abstract":"Measuring user's trust in technology in real-time using psychophysiological signals depends on the availability of stable, accurate, variance sensitive, and non-bias trust classifier model which can be achieved through ensembling several algorithms. Prior efforts resulted to fairly accurate but unstable models. This article investigates what ensemble method is most suitable for developing an ensemble trust classifier model for assessing users trust in technology with psychophysiological signals. Using a self-driving car game, a within subject four condition experiment was implemented. During which 31 participant were involved, and multimodal psychophysiological data (EEG, ECG, EDA, and Facial-EMG) were recorded. An exhaustive 172 features from time and frequency domain were extracted. Six carefully selected algorithms were combined for developing ensemble trust classifier models using each of the four ensemble methods (voting, bagging, stacking, boosting). The result indicated that the Stack ensemble method was more superior, despite voting method dominating prior studies.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123992025","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
Incremental Parameter Estimation of Stochastic State-Based Models 基于随机状态模型的增量参数估计
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378693
R. Lipp, A. Schmeink, Guido Dartmann, L. Fazlic, T. Vollmer, S. Winter, A. Peine, Lukas Martin
{"title":"Incremental Parameter Estimation of Stochastic State-Based Models","authors":"R. Lipp, A. Schmeink, Guido Dartmann, L. Fazlic, T. Vollmer, S. Winter, A. Peine, Lukas Martin","doi":"10.1109/SAMI50585.2021.9378693","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378693","url":null,"abstract":"This paper presents an incremental learning approach for estimating the structural parameters in stochastic state-based models (SSMs). SSMs have proven to be useful for modelling biological and medical processes, as they can represent both time dependency and stochastic processes. A major challenge in modelling in bioinformatics is that learning processes usually rely on large publicly accessible databases. In this work, a new approach is presented, where models are trained incrementally locally at different data sources, e.g., hospitals, without having to pass on sensitive data. After learning, only the parameters of the model are passed on, in this case the arc weights of stochastic Petri nets. As a result, data protection and privacy of patients in hospitals are respected and it is no longer necessary to rely on the existence of a suitable accessible database. Simulations are used to evaluate the performance of the algorithm for a gene regulatory network.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121516543","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
Segmentation of Brain Tissues from Infant MRI Records Using Machine Learning Techniques 使用机器学习技术从婴儿MRI记录中分割脑组织
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378653
Béla Surányi, L. Kovács, L. Szilágyi
{"title":"Segmentation of Brain Tissues from Infant MRI Records Using Machine Learning Techniques","authors":"Béla Surányi, L. Kovács, L. Szilágyi","doi":"10.1109/SAMI50585.2021.9378653","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378653","url":null,"abstract":"The automatic segmentation of medical images is an intensely investigated problem, due to the quick rise of medical image data amount created day by day, which cannot be followed by the number of human experts. This paper searches for the most suitable classical machine learning method to be employed in the segmentation of various tissue types from volumetric multi-spectral MRI records of 6-month infant patients. Model training and model based prediction is performed using the 10 records of the train data set available at the iSeg-2017 challenge. All MRI records are treated with histogram normalization and feature generation, and then fed to six machine learning methods, which use them as train and test data according to the leave-one-out technique. The output of the classification algorithms is evaluated with statistical methods. The best segmentation accuracy is achieved by the random forest based approach, with a correct decision rate of 83.4%.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127530032","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
Occlusion Handling in Generic Object Detection: A Review 一般目标检测中的遮挡处理:综述
2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 2021-01-21 DOI: 10.1109/SAMI50585.2021.9378657
Kaziwa Saleh, S. Szénási, Z. Vámossy
{"title":"Occlusion Handling in Generic Object Detection: A Review","authors":"Kaziwa Saleh, S. Szénási, Z. Vámossy","doi":"10.1109/SAMI50585.2021.9378657","DOIUrl":"https://doi.org/10.1109/SAMI50585.2021.9378657","url":null,"abstract":"The significant power of deep learning networks has led to enormous development in object detection. Over the last few years, object detector frameworks have achieved tremendous success in both accuracy and efficiency. However, their ability is far from that of human beings due to several factors, occlusion being one of them. Since occlusion can happen in various locations, scale, and ratio, it is very difficult to handle. In this paper, we address the challenges in occlusion handling in generic object detection in both outdoor and indoor scenes, then we refer to the recent works that have been carried out to overcome these challenges. Finally, we discuss some possible future directions of research.","PeriodicalId":402414,"journal":{"name":"2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129061839","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: 22
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信