检索结果-内蒙古大学图书馆

Towards a Prosodic Model for Synthesized Speech of Mathematical Expressions in MathML 2020

Towards a Prosodic Model for Synthesized Speech of Mathemati...

9th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion

作者： Adriana Souza Diamantino Freitas Doctoral Program in Digital Media Faculty of Engineering - University of Porto Porto Portugal Bahia Federal Institute of Education Science and Technology Porto Seguro Brazil BR Department of Electrical and Computer EngineeringFaculty of Engineering - University of PortoPorto Portugal PT

ISBN: (纸本)9781450389372

The use of the MathML language made possible to improve the accessibility of mathematics for blind or low-vision persons in digital media. Synthetic speech technologies have advanced significantly using MathML, however, the speech synthesizers' standard reading style is still not suitable for mathematics. Making mathematical reading of the speech synthesizers more natural and expressive is still a challenge. The creation of models to produce the appropriate prosody in the synthesized speech of math content is therefore necessary, as shown in previous research. This article presents a proposal for a model to improve prosody in the synthesized speech of mathematical expressions based on MathML. A corpus of mathematical expressions spoken by Mathematics teachers was created to support the model's development. The Fujisaki intonation model was adopted for intonation control, accent and phrase commands have been extracted from the corpus, and some adjustments have been made to manipulate prosodic parameters in the speech of mathematical expression in correlation with the MathML tree; additionally, a pattern of pauses control is being created.

关键词： Accessibility Mathematics Visual Impairment

来源：评论

学校读者我要写书评

暂无评论

Hierarchical deep CNN feature set-based representation learning for robust cross-resolution face recognition

arXiv

引用

arXiv 2021年

作者： Gao, Guangwei Yu, Yi Yang, Jian Qi, Guo-Jun Yang, Meng Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210023 China Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo101-8430 Japan School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China Department of Computer Science University of Central Florida OrlandoFL32816 United States School of Data and Computer Science Sun Yat-sen University Guangzhou510006 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Sun Yat-sen University Guangzhou510006 China

Cross-resolution face recognition (CRFR), which is important in intelligent surveillance and biometric forensics, refers to the problem of matching a low-resolution (LR) probe face image against high-resolution (HR) gallery face images. Existing shallow learning-based and deep learning-based methods focus on mapping the HR-LR face pairs into a joint feature space where the resolution discrepancy is mitigated. However, little works consider how to extract and utilize the intermediate discriminative features from the noisy LR query faces to further mitigate the resolution discrepancy due to the resolution limitations. In this study, we desire to fully exploit the multilevel deep convolutional neural network (CNN) feature set for robust CRFR. In particular, our contributions are threefold. (i) To learn more robust and discriminative features, we desire to adaptively fuse the contextual features from different layers. (ii) To fully exploit these contextual features, we design a feature set-based representation learning (FSRL) scheme to collaboratively represent the hierarchical features for more accurate recognition. Moreover, FSRL utilizes the primitive form of feature maps to keep the latent structural information, especially in noisy cases. (iii) To further promote the recognition performance, we desire to fuse the hierarchical recognition outputs from different stages. Meanwhile, the discriminability from different scales can also be fully integrated. By exploiting these advantages, the efficiency of the proposed method can be delivered. Experimental results on several face datasets have verified the superiority of the presented algorithm to the other competitive CRFR approaches. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

A novel evolution-based recommendation system 12

A novel evolution-based recommendation system

引用

12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Chen, Yi-Cheng Chu, Yen-Lung Hui, Lin Chen, Sheng-Chih Thaipisutikul, Tipajin Weng, Kai-Ze Department of Information Management National Central University Taiwan Department of Computer Science and Information Engineering Tamkang University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9781728128207

Matrix factorization (MF) technique has been widely utilized in recommendation systems due to the precise prediction of users' interests. Prior MF-based methods adapt the overall rating to make the recommendation by extracting latent factors from users and items. However, in real applications, people's preferences usually vary with time;the traditional MF-based methods could not properly capture the change of users' interests. In this paper, by incorporating the recurrent neural network (RNN) into MF, we develop a novel recommendation system, M-RNN-F, to effectively describe the preference evolution of users over time. A learning model is proposed to capture the evolution pattern and predict the user preference in the future. The experimental results show that M-RNN-F performs better than other state-of-the-art recommendation algorithms. In addition, we conduct the experiments on real world dataset to demonstrate the practicability. © 2019 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

FBSNet: A fast bilateral symmetrical network for real-time semantic segmentation

arXiv

引用

arXiv 2021年

作者： Gao, Guangwei Xu, Guoan Li, Juncheng Yu, Yi Lu, Huimin Yang, Jian Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo Japan College of Automation Nanjing University of Posts and Telecommunications Nanjing China Center for Mathematical Artificial Intelligence Department of Mathematics The Chinese University of Hong Kong Hong Kong Hong Kong Kyushu Institute of Technology Kitakyushu804-8550 Japan School of Computer Science and Technology Nanjing University of Science and Technology Nanjing China

Real-time semantic segmentation, which can be visually understood as the pixel-level classification task on the input image, currently has broad application prospects, especially in the fast-developing fields of autonomous driving and drone navigation. However, the huge burden of calculation together with redundant parameters are still the obstacles to its technological development. In this paper, we propose a Fast Bilateral Symmetrical Network (FBSNet) to alleviate the above challenges. Specifically, FBSNet employs a symmetrical encoder-decoder structure with two branches, semantic information branch and spatial detail branch. The semantic information branch is the main branch with deep network architecture to acquire the contextual information of the input image and meanwhile acquire sufficient receptive field. While spatial detail branch is shallow and simple network used to establish local dependencies of each pixel for preserving details, which is essential for restoring the original resolution during the decoding phase. Meanwhile, a feature aggregation module (FAM) is designed to effectively combine the output features of the two branches. The experimental results of Cityscapes and CamVid show that the proposed FBSNet can strike a good balance between accuracy and efficiency. Specifically, it obtains 70.9% and 68.9% mIoU along with the inference speed of 90 fps and 120 fps on these two test datasets, respectively, with only 0.62 million parameters on a single RTX 2080Ti GPU. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Cryptanalysis and improvement of the measurement-device-independent quantum key distribution with hyper-encoding

引用

Modern Physics Letters A 2022年第31期37卷

作者： Lin, Jason Tsai, Chia-Wei Yang, Chun-Wei Department of Computer Science and Engineering National Chung Hsing University No. 145 Xingda Rd. South District Taichung 40227 Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology No. 129 Sec. 3 Sanmin Rd. North District Taichung 40401 Taiwan Master Program for Digital Health Innovation College of Humanities and Sciences China Medical University No. 100 Sec. 1 Jingmao Rd. Beitun District Taichung 406040 Taiwan

Recently, Cui et al. [Sci. China Phys. 62, 110311 (2019)] proposed a measurement-device-independent quantum key distribution (MDI-QKD) scheme based on high-dimensional encoding to increase the channel capacity of each individual photon. A secret key is shared among two legitimate parties via the help of a dishonest third-party (TP). They claimed that the proposed protocol can improve the drawback of the low-key generation rate that existed in the past MDI-QKD schemes. However, this study pointed out a loophole during the security check of TP. That is, the two legitimate participants merely use the corresponding qubit pairs that are both generated in the diagonal basis for the discussion, which leads to a potential attack that not only allows TP to avoid the security check but also creates partial inconsistency of key bits for both communicating sides. Fortunately, this problem can be fixed by a minor correction of the protocol. © World Scientific Publishing Company.

关键词： dishonest third party Measurement-device-independent quantum cryptography quantum key distribution

来源：评论

学校读者我要写书评

暂无评论

A Study on computer Vision Techniques for Self-driving Cars 6th

A Study on Computer Vision Techniques for Self-driving Cars

引用

6th International Conference on Frontier Computing, FC 2018

作者： Agarwal, Nakul Chiang, Cheng-Wei Sharma, Abhishek Department of Computer Science and Engineering The LNM Institute of Information Technology Jaipur India Department of Digital Content Design Ling Tung University Taichung Taiwan Department of Electronics and Communication Engineering and L-CST The LNM Institute of Information Technology JaipurRajasthan India

ISBN: (纸本)9789811336478

Self-driving cars have become inevitable to be present in a near future. A big number of large companies, startups and research groups have been working for years to fulfil the vision of an absolute unmanned transportation system. These systems have the capacity to model how our future societies and livelihood will be shaped. The utopian dream may still be years away, but current researchers have been shaping up for this tomorrow little by little. From a rise and advances in the field of deep learning, there has been a major push received, especially in the field of computer vision and its possibly uncountable applications. Autonomous vehicles have grown a lot over the past decade from development of better computer vision algorithms for solving common driving tasks, to coming up with large datasets which support training of such systems. In this paper, we have aimed to give a brief introduction to research trends being followed in the overlapping areas of self-driving cars and computer vision. Some state of the art algorithms for solving some common problems which an autonomous system can be benefitted from, such as object detection and semantic scene segmentation, are also discussed. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar

引用

Smart Health 2024年 34卷

作者： Chokphukhiao, Chaturapron Pattaranit, Pattrawan Tun, Wonn Shweyi Thet Masa, Sakaowrat Leemananil, Rattikorn Natteerapong, Nuttaphorn Phetcharaburanin, Jutarop Boonlue, Sophon Sunat, Khamron Patramanon, Rina Information Technology International Program College of Computing Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Digital Innovation Faculty of Education Khon Kaen University Khon Kaen 40002 Thailand Integrative Biomedical Informatics and Computational Imaging Center I-BIC Faculty of Associated Medical Science Khon Kaen University Khon Kaen 40002 Thailand Department of System Biosciences and Computational Medicine Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Khon Kaen University National Phenome Institute Khon Kaen University Khon Kaen 40002 Thailand Department of Biochemistry Faculty of Science. Khon Kaen University Khon Kaen 40002 Thailand Department of Microbiology Faculty of Science Khon Kaen University Khon Kaen 40002 Thailand Department of Computer Science College of Computing Khon Kaen University 40002 Thailand

Introduction: The use of modern technologies has become crucial for enhancing people's awareness of health problems. By early health risk detection, there will be better treatment outcomes, the severity of illness will decrease, and costs for treatment will also reduce. Performing routine checkups could help patients feel less anxious about their health in the future. In this study, the innovation of “digital Health Avatar” enables users to monitor physical changes, raise awareness of medical conditions, and encourage healthy behaviors by visualizing health status as a 3D figure. Methods: Health data were collected using medical devices like blood test strips, body composition meters, and automatic blood pressure monitors. API technology and cloud computing systems were used to process these collected data and produced a three-dimensional avatar that indicated the user's health status. User satisfaction survey on using the health avatar system was assessed through a survey of 61 participants. Results: Health avatar system successfully generate the data and display the measurement results on the health report page of the system. Users can easily check and record their physiological conditions through the avatar. Moreover, users showed satisfaction on the use of the health avatar system and its effectiveness in health check-ups in the survey. Conclusions: The ‘digital Health Avatar’ has the potential to significantly promote individual well-being and health awareness. Its development will be improved by user feedback and continued study, ensuring it becomes an efficient tool for promoting healthier lifestyles. © 2024 The Authors

关键词： digital health avatar Health sensors Healthcare Three-dimensional model

来源：评论

学校读者我要写书评

暂无评论

No winners: Performance of lung cancer prediction models depends on screening-detected, incidental, and biopsied pulmonary nodule use cases.

arXiv

引用

arXiv 2024年

作者： Li, Thomas Z. Xu, Kaiwen Krishnan, Aravind Gao, Riqiang Kammer, Michael N. Antic, Sanja Xiao, David Knight, Michael Martinez, Yency Paez, Rafael Lentz, Robert J. Deppen, Stephen Grogan, Eric L. Lasko, Thomas A. Sandler, Kim L. Maldonado, Fabien Landman, Bennett A. Medical Scientist Training Program Vanderbilt University NashvilleTN37235 United States Biomedical Engineering Vanderbilt University NashvilleTN37235 United States Computer Science Vanderbilt University NashvilleTN37235 United States Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Digital Technology and Innovation Siemens Healthineers PrincetonNJ08540 United States Division of Allergy Pulmonary and Critical Care Medicine Department of Medicine Vanderbilt University Medical Center NashvilleTN37232 United States Department of Thoracic Surgery Vanderbilt University Medical Center NashvilleTN37232 United States Biomedical Informatics Vanderbilt University Medical Center NashvilleTN37232 United States Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN37232 United States

Purpose: Statistical models for predicting lung cancer have the potential to facilitate earlier diagnosis of malignancy and avoid invasive workup of benign disease. Many models have been published, but comparative studies of their utility in different clinical settings in which patients would arguably most benefit are scarce. Materials and Methods: This study retrospectively evaluated promising predictive models for lung cancer prediction in three clinical settings: lung cancer screening with low-dose computed tomography, incidentally detected pulmonary nodules, and nodules deemed suspicious enough to warrant a biopsy. We leveraged 9 cohorts (n=898, 896, 882, 219, 364, 117, 131, 115, 373) from multiple institutions to assess the area under the receiver operating characteristic curve (AUC) of validated models including logistic regressions on clinical variables and radiologist nodule characterizations, artificial intelligence on chest CTs, longitudinal imaging AI, and multi-modal approaches. We implemented each model from their published literature, re-training the models if necessary, and curated each cohort from primary data sources. Results: We observed that model performance varied greatly across clinical use cases. No single predictive model emerged as a clear winner across all cohorts, but certain models excelled in specific clinical contexts. Single timepoint chest CT AI performed well in lung screening, but struggled to generalize to other clinical settings. Longitudinal imaging and multimodal models demonstrated comparatively promising performance on incidentally-detected nodules. However, when applied to nodules that underwent biopsy, all models underperformed. Conclusion: These results underscore the strengths and limitations of 8 validated predictive models and highlight promising directions towards personalized, noninvasive lung cancer diagnosis. © 2024, CC BY-NC-SA.

关键词： Biopsy

来源：评论

学校读者我要写书评

暂无评论

The matter of deep reinforcement learning towards practical ai applications 12

The matter of deep reinforcement learning towards practical ...

引用

12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Thaipisutikul, Tipajin Chen, Yi-Cheng Hui, Lin Chen, Sheng-Chih Mongkolwat, Pattanasak Shih, Timothy K. Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Management National Central University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Faculty of Information and Communication Technology Mahidol University Thailand

ISBN: (纸本)9781728128207

Reinforcement Learning (RL) is an extraordinarily paradigm that aims to solve a complex problem. This technique leverages the traditional feedforward networks with temporal-difference learning to overcome supervised and unsupervised real-world problems. However, RL is one of state-of-the-art topic due to the opaque aspects in design and implementation. Also, in which situation we will get performance gain from RL is still unclear. Therefore, This study firstly examines the impact of Experience Replay in Deep Q-Learning agent with Self-Driving Car application. Secondly, The impact of Eligibility Trace in RNN A3C agents with Breakout AI game application is studied. Our results indicated that these two techniques enhance RL performance by more than 20 percent as compared with traditional RL methods. © 2019 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

The IDEAL framework for surgical robotics: development, comparative evaluation and long-term monitoring (vol 30, pg 61, 2024)

引用

NATURE MEDICINE 2024年第4期30卷 1213-1213页

作者： Marcus, Hani J. Ramirez, Pedro T. Khan, Danyal Z. Horsfall, Hugo Layard Hanrahan, John G. Williams, Simon C. Beard, David J. Bhat, Rani Catchpole, Ken Cook, Andrew Hutchison, Katrina Martin, Janet Melvin, Tom Stoyanov, Danail Rovers, Maroeska Raison, Nicholas Dasgupta, Prokar Noonan, David Stocken, Deborah Sturt, Georgia Vanhoestenberghe, Anne Vasey, Baptiste McCulloch, Peter Department of Neurosurgery National Hospital of Neurology and Neurosurgery London UK Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS) London UK Department of Obstetrics and Gynaecology Houston Methodist Hospital Neal Cancer Center Houston TX USA RCS Surgical Interventional Trials Unit (SITU) & Robotic and Digital Surgery Initiative (RADAR) Nuffield Dept Orthopaedics Rheumatology and Musculo-skeletal Sciences University of Oxford Oxford UK Department of Gynaecological Oncology Apollo Hospital Bengaluru India Department of Anaesthesia and Perioperative Medicine Medical University of South Carolina Charleston SC USA NIHR Coordinating Centre and Clinical Trials Unit University of Southampton Southampton UK Department of Philosophy Macquarie University Sydney Australia Department of Anesthesia & Perioperative Medicine University of Western Ontario Ontario Canada Department of Medical Gerontology School of Medicine Trinity College Dublin Dublin Republic of Ireland Department of Medical Imaging Radboudumc Nijmegen the Netherlands Department of Biomedical Engineering and Imaging Sciences King’s College London London UK King’s Health Partners Academic Surgery King’s College London London UK Moon Surgical Paris France RCSEng Surgical Trials Centre Leeds Institute of Clinical Trials Research University of Leeds Leeds UK Bowel Research UK London UK School of Biomedical Engineering & Imaging Sciences King’s College London London UK Department of Surgery Geneva University Hospital Geneva Switzerland Nuffield Department of Surgical Sciences University of Oxford John Radcliffe Hospital Oxford UK PRISMA Lab University of Naples Federico II Naples Italy Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich Switzerland School of Computer Science University of Birmingham Birmingham UK Division of Cardiac Surgery Brigham and Women’s Hospital Harvard Medical Schoo

The next generation of surgical robotics is poised to disrupt healthcare systems worldwide, requiring new frameworks for evaluation. However, evaluation during a surgical robot’s development is challenging due to their complex evolving nature, potential for wider system disruption and integration with complementary technologies like artificial intelligence. Comparative clinical studies require attention to intervention context, learning curves and standardized outcomes. Long-term monitoring needs to transition toward collaborative, transparent and inclusive consortiums for real-world data collection. Here, the Idea, Development, Exploration, Assessment and Long-term monitoring (IDEAL) Robotics Colloquium proposes recommendations for evaluation during development, comparative study and clinical monitoring of surgical robots—providing practical recommendations for developers, clinicians, patients and healthcare systems. Multiple perspectives are considered, including economics, surgical training, human factors, ethics, patient perspectives and sustainability. Further work is needed on standardized metrics, health economic assessment models and global applicability of recommendations.

关键词： Medical research Surgery

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：