检索结果-内蒙古大学图书馆

IEEE International Conference on Consumer Electronics (ICCE)

作者： Yuya Masuda Hiroshi Ishikawa Department of Computer Science and Communications Engineering Waseda University Tokyo Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

We propose the task of partial super-resolution and introduce two methods for the task, PartialHAT and Partial- DRCT. Partial super-resolution is the task of enhancing the resolution of a specific region of an image. For this task, we incorporated cross attention and a novel loss function into the existing super-resolution models, HAT and DRCT. Experimental results demonstrate that our approach outperforms the original methods, HAT and DRCT, in terms of PSNR. Additionally, we conducted experiments by altering the hyperparameter values of the loss function. Our source code is available at https://***/msdsm/partial-super-resolution.

关键词： Source coding Superresolution Consumer electronics

来源：评论

学校读者我要写书评

暂无评论

Human Avatar Generation Using 3D Gaussian Splatting With a Focus on Non-Rigid Deformations

Human Avatar Generation Using 3D Gaussian Splatting With a F...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Taketo Kato Yiming Liang Hiroshi Ishikawa Department of Computer Science and Communications Engineering Waseda University Tokyo Japan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

This paper proposes a method for reconstructing clothed humans based on 3D Gaussian Splatting (3DGS). Applying static 3DGS to the dynamic problem of human reconstruction is challenging due to the complexity of non-rigid deformations and detailed representation of clothing. To address these issues, we optimized 3DGS to align with non-rigid transformations based on the Splatting Avatar technique. As a result, our method enabled the generation of novel view images with better PSNR accuracy compared to the Splatting Avatar method.

关键词： Training Deformable models Solid modeling Three-dimensional displays Accuracy Deformation Avatars Predictive models Image reconstruction Optimization

来源：评论

学校读者我要写书评

暂无评论

Efficient Video Super-Resolution via Two-Step 2D SR and Image-to-Image Conditional Generation

Efficient Video Super-Resolution via Two-Step 2D SR and Imag...

引用

International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Yuya Masuda Shunta Shimizu Hiroshi Ishikawa Department of Computer Science and Communications Engineering Waseda University Tokyo Japan

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

Video super-resolution (VSR) has gained significant attention due to its potential to enhance video quality. However, existing VSR models are often computationally heavy, limiting their practical application. To address this, we propose a two-step approach: applying 2D super-resolution (SR) followed by image-to-image conditional generation. Initial experiments using Mean Squared Error (MSE) show significant improvements. Replacing MSE with Mean Absolute Error (MAE) and blending it with Structural Similarity Index Measure (SSIM) further enhances performance. Our method achieves superior results with reduced computational complexity, offering a practical solution for real-world VSR applications. Our code is available at https://***/msdsm/efficient-video-sr-2steps.

关键词： Visualization Limiting Computational modeling Superresolution Measurement uncertainty Loss measurement Quality assessment Indexes Computational complexity Video recording

来源：评论

学校读者我要写书评

暂无评论

Leveraging Data from Vast Unexplored Seas: Positive Unlabeled Learning for Refining Prediction Area in Good Fishing Ground Prediction 27th

Leveraging Data from Vast Unexplored Seas: Positive Unlabel...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Konii, Haruki Nakano, Teppei Miyazawa, Yasumasa Ogawa, Tetsuji Department of Communications and Computer Engineering Waseda University Tokyo Japan Intelligent Framework Laboratory Tokyo Japan Application Laboratory Japan Agency for Marine-Earth Science and Technology Yokohama Japan

ISBN: (纸本)9783031781919

This paper proposes a Positive Unlabeled (PU) learning approach to narrow down the prediction area in the context of good fishing ground prediction. PU learning, a type of semi-supervised learning, is particularly suitable for scenarios characterized by limited positive examples and abundant unlabeled data, as often encountered in fishing ground prediction tasks, where the explored sea areas identified as productive fishing spots are treated as positive instances and the vast unexplored sea areas as unlabeled data. Conventional methods often struggle to accurately model the characteristics of good fishing grounds, resulting in overly broad prediction areas or overly restrictive constraints. To tackle this challenge, we present a PU learning-based method designed to identify negative examples from the unlabeled data and consequently refine the area predicted as positive. Specifically, we train a prediction model for fishing duration, which can be considered a surrogate indicator of good fishing grounds. Subsequently, we apply this model to predict the fishing duration for unexplored areas;those areas exhibiting short fishing durations are deemed reliable negative examples. By incorporating both past positive examples and selected negative examples into a binary classification framework for predicting good fishing grounds, we aim to fine-tune the prediction area. To the best of our knowledge, this study represents the first application of PU learning in the domain of good fishing ground prediction. Experimental comparisons conducted using data from bullet tuna trolling validate the efficacy of the proposed methodology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Shoe-Based PDR System for Two-Dimensional Tracking

Shoe-Based PDR System for Two-Dimensional Tracking

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Dai Kajimoto Yusuke Tanaka Siya Bao Nozomu Togawa Department of Computer Science and Communications Engineering Waseda University Ashirase Corporation

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

The most famous absolute self-positioning is GPS (Global Positioning System). However, GPS cannot be used in indoor and underground environments. Thus, relative positioning methods such as sensor-based pedestrian dead reckoning (PDR) are required. The visually impaired has difficulty using navigation devices using visual information, such as smartphones, and it is necessary to develop navigation devices using non-visual information. In this paper, we propose a highly accurate two-dimensional PDR using Ashirase device, a shoe-based wearable sensor. This sensor provides non-visual navigation aids through the underfoot vibrations and has an accurate position estimation as the sensor is strongly attached to the shoe. The proposed method obtained a low estimation error <0.2% walking in straight lines and <1.2% walking in circles.

关键词： Legged locomotion Vibrations Visualization Accuracy Pedestrians Dead reckoning Wearable devices Wearable sensors Smart phones Global Positioning System

来源：评论

学校读者我要写书评

暂无评论

When Generative AI Meets Semantic Communication: Optimizing Radio Map Construction and Distribution in Future Mobile Networks

引用

IEEE Network 2025年第3期39卷 47-55页

作者： Zhou, Li Deng, Xinfeng Ning, Zhaolong Zhao, Haitao Wei, Jibo Leung, Victor C. M. National University of Defense Technology College of Electronic Science and Technology Changsha410073 China Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China Shenzhen MSU-BIT University AI Research Institute Shenzhen518000 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518000 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

With the rapid development of the internet of things and smart cities, the demand for effective spectrum collaboration has grown *** maps play a crucial role in understanding the spatial radio environment, which is essential for wireless applications such as cell planning and radio resource management. However, generating radio maps is a resource-intensive task, as the construction process is complex and the distribution process consumes substantial bandwidth. This article proposes a method that combines semantic communication (SemCom) and generative artificial intelligence (GAI) to optimize the construction and distribution processes of radio maps. By incorporating SemCom, our method transmits only key semantic information during the distribution process, significantly reducing bandwidth usage while ensuring accurate and efficient information transfer. While the diverse generative capabilities of GAI introduce some instability, which could be a limitation in radio map construction, this article achieves precise content decoding through prompts based on multi-modal semantic information, enabling accurate construction and restoration of radio maps. By utilizing SemCom and GAI technologies, the cost of applications of radio maps can be significantly reduced, which is beneficial for stimulating the pace of intelligence evolution in future mobile networks. © 1986-2012 IEEE.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Low crosstalk and high extinction ratio all-optical 4 × 2 encoder based on metal–insulator–metal plasmonic waveguides

引用

Optical and Quantum Electronics 2025年第4期57卷 1-14页

作者： Qiaoling, Tang Afshari-Bavil, Mehdi Rezaei, Mir Hamid School of Physics and Electronic Information Engineering Neijiang Normal University Sichuan Province Neijiang641112 China Photonics Research Center Neijiang Normal University Sichuan Province Neijiang641112 China Department of Communications and Electronics School of Electrical and Computer Engineering Shiraz University Shiraz Iran

This paper presents an all-optical 4 × 2 encoder based on metal–insulator–metal (MIM) waveguides, designed for operation across a wide wavelength range of 1–2 μm. The MIM waveguides consist of SiO2 dielectric strips sandwiched between layers of silver metal. The encoder incorporates a straight waveguide to detect the state of the In0 input. Additionally, it includes one splitter and two combiners with outputs Out0 and Out1 for detecting the states of the In1, In2, and In3 inputs. A key innovation in this work is the distance created between the splitter and combiners, which allows for tuning and improving the encoder output characteristics. The proposed encoder was simulated using the finite-difference time-domain method. It demonstrates a minimum extinction ratio of 11.65 dB and a crosstalk level of − 15.65 dB at a wavelength of 1550 nm. The total footprint of the encoder is less than 8 μm2. Our research indicates that a 4 × 2 encoder utilizing MIM waveguides has not been previously reported. Given its straightforward fabrication process, high extinction ratio, and low crosstalk, the suggested encoder is a promising candidate for a wide range of plasmonic communication and signal-processing applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Crosstalk

来源：评论

学校读者我要写书评

暂无评论

A Developer-Focused Genetic Algorithm for IoT Application Placement in the Computing Continuum

引用

IEEE Transactions on Services Computing 2025年

作者： Herrera, Juan Luis Moya, Alejandro Berrocal, Javier Murillo, Juan Manuel Navarro, Elena University of Bologna Department of Computer Science Engineering Italy University of Castilla-La Mancha LoUISE Research Group Spain University of Extremadura Department of Computer Science and Communications Engineering Spain

The rise of the Internet of Things (IoT) paradigm has led to an interest in applying it not only in tasks for the general public but also to stringent domains such as healthcare. However, the developers of these next-generation IoT applications must consider additional non-functional requirements related to the criticality of the processes they automate, such as low response times or low deployment costs, as well as technical constraints, which include organizational, legal and policy-related constraints on where data can be processed or stored. While the Computing Continuum paradigm emerges as a valuable alternative for placing such applications, identifying the deployments that satisfy all these requirements becomes a tough challenge. The NP-hard nature of the problem makes it impractical to manually find such a deployment, and traditional approaches fail to consider the technical constraints. In this paper, we present the Genetic Algorithm for Application Placement (GAAP), an evolutionary computing-based meta-heuristic designed to help IoT application developers find deployments that satisfy their Quality of Service, business and technical constraints. Our evaluation of an Internet of Medical Things use case shows that GAAP supports larger scenarios than traditional approaches and gives IoT application developers more options while providing better scalability. © 2008-2012 IEEE.

关键词： Computing Continuum Deployment Genetic Algorithm Internet of Things Quality of Service Service Placement

来源：评论

学校读者我要写书评

暂无评论

Self–triggered Scheme Design for Takagi–Sugeno Fuzzy Model based on Mismatch Premise Variable With Time–varying Delay

引用

IEEE Transactions on Automation Science and engineering 2025年 22卷 15536-15548页

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Vasilakos, Athanasios V. China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou2211106 China College of Mechatronics and Control Engineering College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China College of Computer Science and Information Technology IAU Department of Networks and Communications P.O. Box 1982 Dammam31441 Saudi Arabia Grimstad Norway

Over the last 20 years, numerous experts in the manufacturing companies have become interested in controlling flexible joint robots. The control design process using a networked framework has played a significant role in the industrial sector. This research addresses the self–triggered control problem for Takagi–Sugeno (T–S) fuzzy systems based on time delay is established in this research. A new self–triggered mechanism determines when the plant state is transmitted. Instead of continuously tracking predefined triggering conditions, the self–triggered system determines the next triggering instant based on the most recently triggered state information. The self–triggered mechanism relying on T–S fuzzy controller is then created using the triggered state, allowing for flexible configuration of its fuzzy rules and membership operations (MOs) that are not dependent on the controlled fuzzy system. Furthermore, it precisely demonstrates the interaction between the triggered condition and the plant state under the constraint of mismatched premise variables. To ensure system stability and performance, delay–dependent requirements are derived using a novel Lyapunov–Krasovskii functional based on fuzzy concepts to develop the fuzzy control design. The presence of the required controller is then shown under LMI–based conditions. Lastly, a simulation of a flexible robotic arm example is provided along with an evaluation of other triggered methods. © 2004-2012 IEEE.

关键词： Industrial plants

来源：评论

学校读者我要写书评

暂无评论

Retinal disorder diagnosis based on hybrid deep learning models

引用

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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：