检索结果-内蒙古大学图书馆

18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Zheng, Yifu Zheng, Xu Wang, Tingqi Mu, Chong Zhakiyev, Nurkhat School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Department of Science and Innovation Astana IT University Astana Kazakhstan

ISBN: (纸本)9783031714665

Personalized Federated Learning (pFL) is among the most popular tasks in distributed deep learning, which compensates for mutual knowledge and enables device-specific model personalization. However, the effectiveness of pFL is severely impeded by challenges on fairness and significant communication overhead, where devices holding essential samples have to devote extensive resources for model training. To address these issues, we introduce the Fair and Communication-Efficient Personalized Federated Learning (FCE-PFL) framework, which harmonizes performance and device fairness while maintaining communication costs. Based on the Dempster-Shafer Theory, FCE-PFL employs assistance and contribution metrics to quantify the auxiliary information a client receives and provides. Then FCE-PFL balances and adjusts the involvement of devices in each training iteration, so as to facilitate fair training by constraining the maximum resource consumption per device and reduce the overall communication overhead. Our framework has been proven to be superior to existing methods in accuracy through rigorous experiments on the CIFAR10 and CIFAR100 datasets, demonstrating its potential as a fair and efficient pFL solution. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Analyzing and Forecasting Dew Point Temperature Trends in Bangladesh 2

Analyzing and Forecasting Dew Point Temperature Trends in Ba...

引用

2nd International Conference on information and Communication technology, ICICT 2024

作者： Abdullah, Md. Waheed, Sajjad Morshed, Monir Hasan, Md. Mahmodul Dept. of Information and Communication Technology Mawlana Bhashani Science and Technology University Tangail Bangladesh Dept of Software Engineering Bangabandhu Sheikh Mujibur Rahman Digital University Kaliakair Bangladesh

ISBN: (纸本)9798331508227

Climate change presents substantial worldwide concerns, especially for regions such as Bangladesh, which are exceptionally susceptible due to their geographical and socioeconomic circumstances. An important parameter of an environment’s weather conditions is the dew point temperature, which significantly influences weather forecasting and climate research. This research intends to expose fundamental trends, seasonal fluctuations, and long-term patterns in the dew point temperature data. The preprocessing steps involved handling missing values, cleaning unnecessary data, and normalizing the dataset to ensure accuracy and consistency. The data was analyzed using correlation analysis, trend analysis, and seasonal decomposition approaches to uncover meaningful insights. In addition, a basic predictive model has been applied to showcase possible forecasting abilities. The results highlight the intricate relationships between dew point temperature and other climatic factors, showcasing both daily and seasonal cycles and long-term trends. The findings of this study are essential information for the development of more accurate and reliable climate models and contribute to a better understanding of climatic changes in Bangladesh. ©2024 IEEE.

关键词： Climate change Climate research Dew Point Temperature Weather forecasting

来源：评论

学校读者我要写书评

暂无评论

Application research of hyperspectral remote sensing in the identification of stratigraphic boundaries alongside growing tunnels 4

Application research of hyperspectral remote sensing in the ...

引用

4th International Conference on Telecommunications, Optics, and Computer Science, TOCS 2023

作者： Bi, Xiaojia Jiang, Liangwen Dong, Qing He, Lei Wang, Dong China Railway ErYuan Engineering Group Co. Ltd Sichuan Chengdu China Beijing China School of Software Engineering Chengdu University of Information Technology Sichuan Chengdu China

ISBN: (数字)9781510679849

ISBN: (纸本)9781510679832

The geological survey along the large railway in China is difficult, the boundaries of many regional geological maps are unclear, and the geological mapping is very different. The use of hyperspectral remote sensing can greatly improve the survey accuracy in complex mountainous areas. In the identification of lithology and structure, hyperspectral remote sensing has certain advantages compared with multi-spectral satellite images. In this paper, the hyperspectral data of Gaofen-5 satellite is interpreted by a series of technical methods, such as data preprocessing, radiometric calibration, atmospheric correction, orthographic correction, image information enhancement, radiation homogenization processing, etc. According to different geological conditions, lithologic structure information by hyperspectral information enhancement technology in different regions and layers. Different geological units are effectively divided, the distribution characteristics of geological structure space are identified, and some stratigraphic boundaries of the original geological map are adjusted. This paper solves the problems that the survey personnel of long and large tunnels cannot reach, and the conventional survey methods cannot verify the stratigraphic boundaries and lithological characteristics. It also provides an important auxiliary reference value for the identification of surrounding rock of hyperspectral remote sensing. © 2024 SPIE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

MACLSTM: A Weather Attributes Enabled Recurrent Approach to Appliance-Level Energy Consumption Forecasting

引用

Computers, Materials & Continua 2025年第2期82卷 2969-2984页

作者： Ruoxin Li Shaoxiong Wu Fengping Deng Zhongli Tian Hua Cai Xiang Li Xu Xu Qi Liu NARI-TECH Nanjing Control System Co. Ltd.Nanjing211106China School of Software Nanjing University of Information Science&TechnologyNanjing210044China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing210044China

Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.

关键词： Electrical load forecasting cloud computing smart grid weather attributes energy consumption time-series analysis

来源：评论

学校读者我要写书评

暂无评论

Research on microseismic source localization based on improved particle swarm optimization algorithm 4

Research on microseismic source localization based on improv...

引用

4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Wan, Yunshuai Xue, Jinchun Qi, Hui Ren, Feipeng Jiangxi University of Science and Technology School of Energy and Mechanical Engineering Nanchang China Jiangxi University of Science and Technology School of Software Engineering Nanchang China Shandong Shenghan Finance and Trade Vocational College School of Information Engineering Jinan China

ISBN: (纸本)9798331531225

Accurate microseismic source localization is crucial for detecting potential geological hazards during mining operations, ensuring the safe and efficient progress of excavation activities. The accuracy and reliability of source localization are closely linked to the selection of appropriate algorithms. While the Particle Swarm Optimization (PSO) algorithm offers the advantage of fast convergence, it is prone to premature convergence and low localization accuracy when directly applied to source localization. To address these issues, this study employs chaotic mapping to replace traditional methods for initializing the particle population, enhancing population diversity. The proposed method is validated through engineering case studies. The results demonstrate that, compared to the traditional PSO algorithm, the chaotic mapping-based improved PSO algorithm achieves faster convergence and superior optimization capabilities, making it suitable for solving practical engineering problems. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Identification of energy facilities in remote sensing images: comparison of single and joint models

Identification of energy facilities in remote sensing images...

引用

2024 International Conference on Remote Sensing, Mapping, and Geographic information Systems, RSMG 2024

作者： Liu, Kun Chen, Xingfeng Zheng, Fengjie Meng, Lei Jiang, Mingyong Li, Zhiliang Li, Kaitao Li, Jiaguo Zhang, Yunli Liu, Shumin School of Software Engineering Jiangxi University of Science and Technology Nanchang330013 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Space Information Space Engineering University Beijing101416 China

ISBN: (纸本)9781510685826

Wind turbines and high-voltage transmission towers, as critical energy facilities, pose certain challenges in detection under extreme weather conditions. To enhance the accuracy of target identification for these two facilities, this study designed an experiment using the YOLOv5-CBAM model, where a mixed dataset of wind turbines and high-voltage transmission towers was trained under this model to create a joint model for combined recognition. Additionally, single models were trained using individual datasets for wind turbines and high-voltage transmission towers to perform independent identifications, the experimental results indicate a clear advantage in accuracy for the independent identification method. Specifically, in the joint model, the accuracy rates for wind turbines and high-voltage transmission towers were 92.1% and 74.1%, respectively, while in the single models, these rates increased to 99% and 92.3%. This improvement is significant for enhancing the performance of automatic monitoring of energy facilities in complex environments. © 2024 SPIE.

关键词： Windmill

来源：评论

学校读者我要写书评

暂无评论

Fusion of speech and handwritten signatures biometrics for person identification

引用

International Journal of Speech technology 2023年第4期26卷 833-850页

作者： Abushariah, Ahmad A. M. Abushariah, Mohammad A. M. Gunawan, Teddy Surya Chebil, J. Alqudah, Assal A. M. Ting, Hua-Nong Mustafa, Mumtaz Begum Peer Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Computer Information Systems King Abdullah II School of Information Technology The University of Jordan Amman Jordan ECE Department Faculty of Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia Department of Computer Science Faculty of Science and Information Technology Al-Zaytoonah University of Jordan Amman Jordan Department of Biomedical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

Automatic person identification (API) using human biometrics is essential and highly demanded compared to traditional API methods, where a person is automatically identified using his/her distinct characteristics including speech, fingerprint, iris, handwritten signatures, and others. The fusion of more than one human biometric produces bimodal and multimodal API systems that normally outperform single modality systems. This paper presents our work towards fusing speech and handwritten signatures for developing a bimodal API system, where fusion was conducted at the decision level due to the differences in the type and format of the features extracted. A data set is created that contains recordings of usernames and handwritten signatures of 100 persons (50 males and 50 females), where each person recorded his/her username 30 times and provided his/her handwritten signature 30 times. Consequently, a total of 3000 utterances and 3000 handwritten signatures were collected. The speech API used Mel-Frequency Cepstral Coefficients (MFCC) technique for features extraction and Vector Quantization (VQ) for features training and classification. On the other hand, the handwritten signatures API used global features for reflecting the structure of the hand signature image such as image area, pure height, pure width and signature height and the Multi-Layer Perceptron (MLP) architecture of Artificial Neural Network for features training and classification. Once the best matches for both the speech and the handwritten signatures API are produced, the fusion process takes place at decision level. It computes the difference between the two best matches for each modality and selects the modality of the maximum difference. Based on our experimental results, the bimodal API obtained an average recognition rate of 96.40%, whereas the speech API and the handwritten signatures API obtained average recognition rates of 92.60% and 75.20%, respectively. Therefore, the bimodal API system is a

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

引用

Computers, Materials & Continua 2023年第7期76卷 573-589页

作者： Halah Hasan Mahmoud Marwan Kadhim Mohammed Al-Shammari Gehad Abdullah Amran Elsayed Tag eldin Ala R.Alareqi Nivin A.Ghamry Ehaa A.Lnajjar Esmail Almosharea Computer Center University of BaghdadBaghdad6751Iraq Department of Management Science and Engineering Dalian University of TechnologyLiaoningDalian116024China Department of Information Technology Faculty of Computer Sciences and Information Technology AL Razi UniversitySana’aYemen Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Faculty of Engineering Mechanics Dalian University of TechnologyLiaoningDalian116024China Faculty of Computers and Artificial Intelligence Cairo UniversityGizaEgypt Department of Business Administration Dalian University of TechnologyLiaoningDalian116024China College of Software Engineering Dalian University of TechnologyChina

Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial *** of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine *** study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity *** Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity *** research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical *** results suggest that detecting the submarine early increases the likelihood of averting a *** dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access *** communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the *** swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its ***,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other *** dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.

关键词： Unmanned vehicles unmanned aerial vehicles unmanned underwater vehicles high altitude unmanned aerial vehicles anti-submarine warfare re-fragmentation dragonfly algorithm

来源：评论

学校读者我要写书评

暂无评论

SlotFusion: Object-Centric Audiovisual Feature Fusion with Slot Attention for Remote Sensing Scene Recognition

SlotFusion: Object-Centric Audiovisual Feature Fusion with S...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Han, Fangzhou Yu, Tianyi Zhang, Lamei Si, Lingyu Zhang, Yiqi Dept. of Information Engineering Harbin Institute of Technology Harbin China National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing China Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350368741

Despite significant advancements in remote sensing multimodal learning, particularly in image-image feature fusion, the exploration of audio-image feature fusion remains insufficient. Given the complexity and redundancy of ground objects in remote sensing images, accurately aligning audio features with image features during the fusion process is a critical challenge. In this paper, we introduce an object-centric feature fusion method named SlotFusion. By employing a slot attention-based feature decoupling module and a slot-based audiovisual feature fusion module, we transform modality features with complex semantic information into a set of slot features corresponding to object units and use gated activation units to adaptively implement object-centric feature fusion. Experiments on the Audio Visual Aerial Scene Recognition dataset (ADVANCE) demonstrate that the proposed SlotFusion significantly improves remote sensing scene recognition performance, with a 7.04% increase in overall accuracy compared to previous methods, achieving state-of-the-art results. © 2025 IEEE.

关键词： Audiovisual feature fusion Gated feature fusion Object-centric learning Slot attention

来源：评论

学校读者我要写书评

暂无评论

Fusion Feature Offsets Estimation Network for 6D Pose Estimation 28

Fusion Feature Offsets Estimation Network for 6D Pose Estima...

引用

28th International Conference on Automation and Computing, ICAC 2023

作者： Lu, Xin Yang, Haibo Jia, Junying Jia, Zhengfeng Wang, Jialin School of Information Science and Engineering Shenyang University of Technology Shenyang China Fengchi Software Research Institute Shenyang Fengchi Software Co.Ltd Shenyang China

ISBN: (纸本)9798350335859

Object pose estimation involves calculating the six degrees of freedom pose of a rigid object. A typical approach involves utilizing convolution neural networks to detect keypoints and subsequently estimating pose from these points. Investigations focused on combining RGB images and point clouds to extract keypoints remain a subject of interest. In this work, we propose an offsets estimation network based on fused features to estimate pose. We first propose a more effective encoding method for fuse image features into point cloud features. Then we design an offsets estimate network to calculate the keypoint's location. Next, we estimate multiple poses according to the keypoints predicted above in two levels. Finally, we aggregate multiple poses into the final pose according to the weight of each pose. Our experiments show that our method outperforms other approaches in the LineMOD benchmark dataset. © 2023 IEEE.

关键词： Degrees of freedom (mechanics)

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：