检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Big Data, BigData 2023

作者： Stragapede, Giuseppe Vera-Rodriguez, Ruben Tolosana, Ruben Morales, Aythami Deandres-Tame, Ivan Damer, Naser Fierrez, Julian Garcia, Javier-Ortega Gonzalez, Nahuel Shadrikov, Andrei Gordin, Dmitrii Schmitt, Leon Wimmer, Daniel Grosmann, Christoph Krieger, Joerdis Heinz, Florian Krestel, Ron Mayer, Christoffer Haberl, Simon Gschrey, Helena Yamagishi, Yosuke Saha, Sanjay Rasnayaka, Sanka Wickramanayake, Sandareka Sim, Terence Gutfeter, Weronika Baran, Adam Krzyszton, Mateusz Jaskola, Przemyslaw Lab Spain Fraunhofer Institute for Computer Graphics Research Igd Darmstadt Germany Argentina Verigram Llc Singapore Citix Almaty Kazakhstan Regensburg University of Applied Sciences Germany The University of Tokyo Division of Radiology and Biomedical Engineering Japan National University of Singapore Singapore University of Moratuwa Sri Lanka Nask - National Research Warsaw Poland

ISBN: (纸本)9798350324457

institute, Warsaw, Poland This paper describes the results of the IEEE BigData 2023 Keystroke Verification Challenge 1 (KVC), that considers the biometric verification performance of Keystroke Dynamics (KD), captured as tweet-long sequences of variable transcript text from over 185,000 subjects. The data are obtained from two of the largest public databases of KD up to date, the Aalto Desktop and Mobile Keystroke Databases, guaranteeing a minimum amount of data per subject, age and gender annotations, absence of corrupted data, and avoiding excessively unbalanced subject distributions with respect to the considered demographic attributes. Several neural architectures were proposed by the participants, leading to global Equal Error Rates (EERs) as low as 3.33% and 3.61% achieved by the best team respectively in the desktop and mobile scenario, outperforming the current state of the art biometric verification performance for KD. Hosted on CodaLab2, the KVC will be made ongoing to represent a useful tool for the research community to compare different approaches under the same experimental conditions and to deepen the knowledge of the field. © 2023 IEEE.

关键词： behavioral biometrics biometric verification challenge Keystroke dynamics KVC

来源：评论

学校读者我要写书评

暂无评论

Wide-range Angle-sensitive Plasmonic Color Printing with a Lossy Resonator

Wide-range Angle-sensitive Plasmonic Color Printing with a L...

引用

CLEO: Applications and Technology, CLEO:A and T 2023 - Part of Conference on Lasers and Electro-Optics 2023

作者： Chowdhury, Sarah N. Simon, Jeffrey Nowak, Michal P. Prokopeva, Ludmila J. Pagadala, Karthik Fruhling, Colton Nyga, Piotr Bravo, Esteban Garcia Kildishev, Alexander V. Shalaev, Vladimir M. Boltasseva, Alexandra School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University 1205 W State St West LafayetteIN47906 United States Institute of Optoelectronics Military University of Technology 2 Kaliskiego St Warsaw00-908 Poland Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Toruń87-100 Poland Department of Computer Graphics Technology Purdue University 401 N. Grant St Knoy Hall West LafayetteIN47907 United States

ISBN: (纸本)9781957171258

We demonstrate a wide gamut of color generation by large-scale, lithography-free, and environment-friendly plasmonic structures with a resolution of 100 µm for macroscopic color printing by utilizing femtosecond laser photomodification of multi-functional optical elements. CLEO 2023 © Optica Publishing Group 2023, © 2023 The Author(s)

关键词：

来源：评论

学校读者我要写书评

暂无评论

Wide-range Angle-sensitive Plasmonic Color Printing with a Lossy Resonator

Wide-range Angle-sensitive Plasmonic Color Printing with a L...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Chowdhury, Sarah N. Simon, Jeffrey Nowak, Michal P. Prokopeva, Ludmila J. Pagadala, Karthik Fruhling, Colton Nyga, Piotr Bravo, Esteban Garcia Kildishev, Alexander V. Shalaev, Vladimir M. School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University 1205 W State St West LafayetteIN47906 United States Institute of Optoelectronics Military University of Technology 2 Kaliskiego St Warsaw00-908 Poland Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Toruń87-100 Poland Department of Computer Graphics Technology Purdue University 401 N. Grant St Knoy Hall West LafayetteIN47907 United States

We demonstrate a wide gamut of color generation by large-scale, lithography-free, and environment-friendly plasmonic structures with a resolution of 100 urn for macroscopic color printing by utilizing femtosecond lase... 详细信息

ISBN: (纸本)9781957171258

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Combining permuted language model and adversarial training for Chinese machine reading comprehension

引用

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10059-10073页

作者： Liu, Jianping Chu, Xintao Wang, Jian Wang, Meng Wang, Yingfei College of Computer Science and Engineering North Minzu University Yinchuan China The Key Laboratory of Images Graphics Intelligent Processing of State Ethnic Affairs Commission North Minzu University Yinchuan China Agricultural Information Institute Chinese Academy of Agricultural Sciences Beijing China

Due to the polysemy and complexity of the Chinese language, Chinese machine reading comprehension has always been a challenging task. To improve the semantic understanding and robustness of Chinese machine reading comprehension models, we propose a model that utilizes adversarial training algorithms and Permuted Language Model (PERT). Firstly, we employ the PERT pre-training model to embed paragraphs and questions into vector space to obtain corresponding sequential representations. Secondly, we use a multi-head self-attention mechanism to extract key textual information from the sequence and employ a Bi-GRU network to semantically fuse the output feature vectors, aiming to learn deep semantic representations in the text. Finally, we introduce perturbations into the model training process. We achieve this by utilizing adversarial training algorithms such as Fast Gradient Method (FGM) and Projected Gradient Descent (PGD). These algorithms generate adversarial samples to enhance the model’s robustness and stability when facing diverse inputs. We conducted comparative experiments on the publicly available Chinese reading comprehension datasets CMRC2018 and DRCD. The experimental results show that our proposed model has achieved significant improvements in both EM and F1-Score compared to the baseline model. To validate the model’s generalization and robustness, we utilized ChatGPT to construct a scientific dataset that includes a large number of domain-specific terms, sentences with mixed Chinese and English, and complex comprehension tasks. Our model also performed remarkably well on the self-built dataset. In conclusion, the proposed model not only effectively enhances the understanding of semantic information in Chinese text but also demonstrates a certain level of generalization capability. © 2024 – IOS Press. All rights reserved.

关键词： Vector spaces

来源：评论

学校读者我要写书评

暂无评论

Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments

Exploring 3D Reconstruction with Drone Images: Advances and ...

引用

Annual Conference of Industrial Electronics Society

作者： Thiago João Miranda Baldivieso Taise Grazielle Da Silva Batista Fabio Suim Chagas Luiz Carlos Pacheco Rodrigues Velho Paulo Fernando Ferreira Rosa Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea/RJ Rio de Janeiro Brazil Department of Science and Industry Systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software—both commercial and open-source—and concluding with a qualitative evaluation of the results.

关键词： Industrial electronics Three-dimensional displays Urban areas Aircraft Image reconstruction Photogrammetry Drones

来源：评论

学校读者我要写书评

暂无评论

On Integral-Based (Transfinite) Laplace Coordinates 10th

On Integral-Based (Transfinite) Laplace Coordinates

引用

10th International Conference on Numerical Geometry, Grid Generation, and Scientific Computing celebrating the 130th anniversary of B. N. Delaunay, NUMGRID 2020

作者： Belyaev, Alexander G. Fayolle, Pierre-Alain Institute of Sensors Signals and Systems School of Engineering & Physical Sciences Heriot-Watt University Edinburgh United Kingdom Computer Graphics Laboratory University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9783030767976

In this theoretical work, we analyze general constructions for integral-based (transfinite, continuous) barycentric coordinates and consider a simple variational principle to arrive at a continuous version of the Laplace barycentric coordinates. We demonstrate how our approach leads to a general description of the integral-based barycentric coordinates and establish links with Dirichlet energy minimization problems for conical surfaces. Both the 2D and 3D cases are studied. An application to a surface generation problem is briefly considered. © 2021, Springer Nature Switzerland AG.

关键词： Laplace transforms

来源：评论

学校读者我要写书评

暂无评论

UAV-based Digital Field Phenotyping for Crop Nitrogen Estimation using RGB Imagery

UAV-based Digital Field Phenotyping for Crop Nitrogen Estima...

引用

2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Patil, Suchitra M Choudhary, Sunita Kholová, Jana Anbazhagan, Krithika Parnandi, Yogesh Gattu, Priyanka Mallayee, Srikanth Ksvv, Prasad Kumar, V Padma Rajalakshmi, P. Chandramouli, Magesh Adinarayana, J. Indian Institute of Technology Bombay Powai Centre of Studies in Resources Engineering Maharashtra Mumbai400076 India Crop Physiology and Modeling Telangana Patancheru502 324 India Czech University of Life Sciences Prague Department of Information Technologies Prague165 00 Czech Republic Indian Institute of Technology Kandi Telangana Hyderabad502285 India International Livestock Research Institute Telangana Patancheru502324 India Purdue University NW Computer Graphics Technology HammondIN46323 United States

ISBN: (纸本)9798350331790

Nitrogen (N) is one of the essential nutrients required for healthy crop growth. Field phenotyping for nitrogen stress symptoms is laborious and time-consuming, that way, it is a major bottleneck in nutrition-inclusive agricultural research. Recent advancements in sensors and image processing facilitate color-based quantification of crop greenness from high-resolution RGB images. In this paper, we present unmanned aerial vehicle (UAV)-based digital field phenotyping for the estimation of crop nitrogen content. For this, we conducted a field experiment during the post-rainy season of 2021 at International Crops Research institute for Semi-Arid Tropics (ICRISAT), Hyderabad, India with long-stature cereal model crop, sorghum (Sorghum bicolor L.) cultivated under three different regimes varying in moisture and soil nitrogen content. A high-resolution RGB sensor (XenmuseX5S) mounted on DJI Matric 210 quadcopter was used for capturing the spatiotemporal imagery. Five different RGB spectrum vegetation indices indicating crop greenness were correlated with ground truth values of crop N content using simple linear regression and stepwise backward regression. With a prediction potential of R2=0.65 and MAE=0.27 for an independent dataset, we present a stepwise backward linear regression model as a promising approach for real-time estimation of the N status of sorghum crop. © 2023 IEEE.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Improving efficiency energy systems-photovoltaic modules and solar collectors in construction 3

Improving efficiency energy systems-photovoltaic modules and...

引用

3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Martynov, Viacheslav Ploskyi, Vitalii Sergeychuk, Oleg Virchenko, Gennadii Usenko, Valery Tereschuk, Mykola Kyiv National University of Construction and Architecture Department of Architectural Constructions Kyiv03037 Ukraine National Technical University of Ukraine «igor Sikorsky Kyiv Polytechnic Institute» Department of Descriptive Geometry Engineering and Computer Graphics Kyiv03056 Ukraine National University «yuri Kondratyuk Poltava Polytechnic» Department of Construction and Civil Engineering Poltava36040 Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

A method is proposed for increasing the efficiency of using energy systems (photovoltaic modules, solar collectors) due to the optimal location on the building envelope. A mathematical and graphical model has been developed, the Gelioopt program has been developed to determine the optimal orientation and area parameters for photovoltaic modules. A method is proposed for a quick graphical determination of the amount of converted solar energy by photovoltaic modules, and solar collectors, depending on the spatial orientation of solar receivers using building drawings. The proposed developments make it possible to simplify the calculation procedure and increase the determining of optimal parameters speed for solar receivers and is a proposed new type of geometric models. © 2022 IEEE.

关键词： Solar power generation

来源：评论

学校读者我要写书评

暂无评论

A driver-in-the-loop co-simulation framework for testing predictive EDAS for commercial vehicles in urban environments

A driver-in-the-loop co-simulation framework for testing pre...

引用

6th International Commercial Vehicle Technology Symposium, CVT 2020

作者： Chada, Sai Krishna Gőrges, Daniel Ebert, Achim Teutsch, Roman Division of Electromobility Department of Electrical and Computer Engineering University of Kaiserslautern Kaiserslautern67663 Germany Computer Graphics and HCI Group Department of Computer Science University of Kaiserslautern Kaiserslautern67663 Germany Institute for Mechanical and Automotive Engineering Department of Mechanical and Process Engineering University of Kaiserslautern Kaiserslautern67663 Germany

ISBN: (纸本)9783658297169

To experience realistic driving scenarios in the virtual simulation environment, strengths of both the traffic simulation and the vehicle simulation tools must be combined. In this paper, a driver-in-the-loop co-simulation framework for testing predictive eco-driving assistance systems (EDAS) for commercial vehicles in urban environments is proposed. The co-simulation is performed by exchanging information between IPG TruckMaker, a vehicle simulation software tailored for commercial vehicles, and SUMO, an open-source software for microscopic traffic simulation. To avoid delays during the data exchange process, time-steps of both the tools are synchronized. The co-simulation environment replicates a bus route in the city of Kaiserslautern along with the corresponding bus stops, traffic lights, road speed limits, pedestrian crossings and road elevation. The stochastic traffic and pedestrian flow in the road network is generated using SUMO. In this work, the co-simulation framework is extended by introducing the driver into the simulation loop. This is achieved by coupling the vehicle simulation tool with a driving simulator, in which the driver controls the ego-vehicle. The proposed framework will serve to test various use-cases of predictive eco-driving assistant systems (EDAS). © Der/die Autor(en), exklusiv lizenziert durch.

关键词： Open source software

来源：评论

学校读者我要写书评

暂无评论

PFMRC: A Unified MRC Framework for Chinese Named Entity Recognition via Semantic Feature Fusion

PFMRC: A Unified MRC Framework for Chinese Named Entity Reco...

引用

Artificial Intelligence, Robotics, and Communication (ICAIRC), IEEE International Conference on

作者： Zhenrong Deng Jinglin Zhang Yannan Xiao Shiwei Wei Guangxi Key Laboratory of Images and Graphics Intelligent Processing Guilin University of Electronic Technology Guilin China Nanning Research Institute Guilin University of Electronic Technology Guilin China School of Computer Science and Engineering Guilin University of Aerospace Technology Guilin China

ISBN: (数字)9798331531225

ISBN: (纸本)9798331531232

The landscape of natural language processing (NLP) has been revolutionized by advancements that enable the upstream training of knowledge-rich models for downstream tasks, particularly named entity recognition (NER). Traditional NER approaches, treating it as a sequence labeling problem, often fail to deeply understand the whole text and to capture syntactic nuances of text. To address these issues, we introduce PFMRC, a novel machine reading comprehension (MRC) framework that leverages the strengths of both contextual semantics and syntactic information for enhanced NER performance. PFMRC employs a dual-pronged feature extraction strategy, utilizing RoBERTa and BiGRU to encode text features for contextual semantic information and representing them as node features of the graph structure, and a weighted embedding representation to translate syntactic dependencies into graph-structured edge features. Our model further incorporates Graph Attention Networks (GAT) to harmonize node and edge features, facilitating a nuanced understanding of text. The integration of prior knowledge and the modeling of intricate syntactic relationships through Graph Attention Networks (GAT) not only improves entity recognition accuracy but also enriches the feature representation, leading to more robust NER outcomes. Extensive experiments on three Chinese datasets demonstrate PFMRC's superior performance over state-of-the-art models.

关键词： Training Accuracy Translation Semantics Refining Named entity recognition Syntactics Feature extraction Solids Robots

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：