检索结果-内蒙古大学图书馆

2024 28th International Conference on Information Technology, IT 2024

作者： Javidi, Kamran Martini, Maria G. Kara, Peter A. School of Computer Science and Mathematics Faculty of Engineering Computing and the Environment Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science Penrhyn Road Campus Kingston upon Thames LondonKT1 2EE United Kingdom Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary

ISBN: (纸本)9798350369618

Light field visualization commonly provides a single content over the entire field of view. However, the angularly-selective nature of the technology enables the simultaneous visualization of different contents at different viewing angles. Yet segmenting the valid viewing area comes with content interference as well in forms of separation zones, resulting invalid viewing domains. In this paper, we introduce a study on the separation zone of split-domain light field visualization. We created a static-content-based scenario in which we split the valid viewing area into two distinct domains, with a separation zone in between them. This was achieved by merging two light field contents in the middle with an instantaneous switch. The resulting visualization on a light field display was captured by a DSLR camera from two viewing distances, and it was compared to the crosstalk effect caused by insufficient angular resolution. © 2024 IEEE.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Machine Learning based Sales Prediction and Characterization using Consumer Perceptions 6

Machine Learning based Sales Prediction and Characterization...

引用

6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022

作者： Sreemathy, J. Prasath, N. Sri Eshwar College of Engineering Department of Computer Science and Engineering Tamilnadu Coimbatore India Srm Institute of Science and Technology School of Computing Department of Networking and Communications Tamilnadu Chennai India

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

In today's age of automated scenarios and digital lifestyle, online shopping has really made its way to everyone's household, with one touch anyone can order the required products. The use of digital marketing over conventional marketing is often favored. It is beneficial to both social media marketing professionals and technicians. When conducting research, one may gain preliminary insights into consumers' perceptions of social media advertisements and online buying habits. Online knowledge exchange allows researchers, academics, and business people to swiftly and easily connect with individuals while conducting searchable mobile brand website research. This research provides a methodical description of a study that only aids consumers in making the optimal smartphone decision for their own parametric needs. A given dataset will be examined utilising machine learning methods, such as brand name predictions with regression and precise results. Groups of people are frequently paid by brands to create internet evaluations, which may be favourable to them or unfavourable to their competitors. © 2022 IEEE.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Optimizing Wireless Sensor Networks in E-Commerce with Message Passing Neural Networks 2

Optimizing Wireless Sensor Networks in E-Commerce with Messa...

引用

2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Jeyaselvi, M. Saravanan, B. Boobalan, M. Ganesha, M. Lamba, Anil Kumar Suganthi, D. Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur India Sri Eshwar College of Engineering Department of Cse Tamilnadu Coimbatore India Vivekanandha College of Engineering for Women Tiruchengode Namakkal India Ajiet Department of Cse Karnataka Mangaluru India Geeta University School of Computer Science and Engineering Haryana India Saveetha College of Liberal Arts and Sciences Simats Department of Computational Intelligence Thandalam Chennai India

ISBN: (纸本)9798350388916

In today's e-commerce landscape, successful logistics management is essential for achieving success. In this post, we will go over how wireless sensor networks (WSNs) can help online stores streamline their logistics. Data collection and real-time monitoring made possible by wireless sensor networks (WSNs) increase supply chain visibility and control. The proposed approach includes both preprocessing and training the model. Part of the preprocessing phase is principal component analysis (PCA), which entails cleaning and transforming raw data into an appropriate format for analysis or model training. Throughout the training, CNN-BiGRU-BiLSTM was continuously utilized. With a 93.46% average accuracy, this innovative method surpasses the BiGRU and BiLSTM. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Deploying Hybrid MAELM Approach for Human Emotion Detection Through Speech and Facial Expressions 3

Deploying Hybrid MAELM Approach for Human Emotion Detection ...

引用

3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Senthil Kumar, K. Rukmani Devi, S. Ranjan, Nidhi Rath, Gitika Indira, G. Nishant, Neerav SRM Institute of Science and Technology School of Computing Department of Networking and Communications College of Engineering and Technology Chennai India SIMATS Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Science Chennai India Computer Engineering Vasantdada Patil Pratishthan's College of Engineering and Visual Arts Mumbai India Marri Laxman Reddy Institute of Technology and Management Department of CSE Hyderabad India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai India Babu Banarasi das University School of Engineering Department of Computer Science and Engineering Lucknow India

ISBN: (纸本)9798350343632

Emotion recognition is one of the most fascinating emerging fields of research. It's useful in a lot of different contexts. Some of the most exciting applications of this technology involve robots' ability to see and communicate with one another. Human emotions can be recognized through both visual and audible cues. Facial expressions are one of the most accurate indicators of a person's emotional state. Data preprocessing, feature extraction, and model training are the first three steps of the proposed methodology. Image resizing, a median filter, noise removal, and histogram equalization are all components of preprocessing. Gaussian mixture models and the gray level co-occurrence matrix are being used for feature extraction. After the extraction of features, models with those features are trained using MA-ELM. The proposed method outperforms PCA and ELM, two of the most popular alternatives. © 2023 IEEE.

关键词： Gaussian Mixture Models(GMM) Gray Level Co-Occurrence Matrix (GLCM) Principal Component Analysis (PCA)

来源：评论

学校读者我要写书评

暂无评论

Enhanced Multidimensional Harmonic Retrieval in MIMO Wireless Channel Sounding

引用

IEEE Internet of Things Journal 2025年第11期12卷 16243-16255页

作者： Zhang, Yanming Xu, Wenchao Jin, A-Long Tang, Tianquan Li, Min Ma, Peifeng Jiang, Lijun Gao, Steven The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Hong Kong The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong Xi'an Jiaotong-Liverpool University Department of Communications and Networking Suzhou China HKU Zhejiang Institute of Research and Innovation Lab for Aerodynamics and Acoustics Hangzhou China Tianjin University School of Microelectronics Tianjin China The Chinese University of Hong Kong Institute of Space and Earth Information Science Department of Geography and Resource Management Hong Kong Hong Kong Missouri University of Science and Technology Department of Electrical and Computer Engineering RollaMO United States

This paper introduces a recursive parallel dynamic mode decomposition (RPDMD) scheme tailored for multidimensional harmonic retrieval (MHR), specifically applied to MIMO wireless channel sounding. The RPDMD algorithm is devised to address the complexities inherent in multidimensional scenarios, leveraging the dynamic mode decomposition (DMD) framework within a recursive parallel structure. Initially, the observed tensorial multidimensional harmonic data is transformed into a two-dimensional matrix format along the r-th dimension. Subsequently, DMD dissects this matrix data into eigenvalues and their associated modes. The real and imaginary components of the DMD eigenvalues yield damping factors and frequencies in the r-th dimension, respectively. Furthermore, recursive DMD is employed to scrutinize each mode independently for parameter retrieval across the remaining dimensions, enabling parallel analysis. Ultimately, this high-dimensional correlated decomposition scheme delivers paired damping factors and frequencies for all tones. Notably, the proposed approach can ascertain the number of tones in undamped sinusoidal signals, making it particularly suitable for MHR even without prior knowledge of the source count. Numerical experiments demonstrate the accuracy and robustness of the RPDMD scheme, with comparative analysis indicating that RPDMD outperforms similar methods, achieving optimal results with minimal mean square error in high signal-to-noise ratio scenarios. This work presents an effective data-driven solution for the MHR problem in MIMO wireless channel sounding. © 2014 IEEE.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

RAPIDEST: A Framework for Obstructive Sleep Apnea Detection

引用

IEEE Transactions on Neural Systems and Rehabilitation engineering 2023年 31卷 387-397页

作者： Lin, Xin-Xue Lin, Phone Yeh, En-Hau Liu, Gi-Ren Lien, Wan-Ching Fang, Yuguang National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Graduate Institute of Networking and Multimedia Institute of Medical Device and Imaging National Taiwan University Internet of Things Research Center Department of Computer Science and Information Engineering Taipei10617 Taiwan National Cheng Kung University Department of Mathematics Tainan City701 Taiwan National Taiwan University Hospital Department of Emergency Medicine Taipei100229 Taiwan College of Medicine National Taiwan University Department of Emergency Medicine Taipei10617 Taiwan City University of HongKong Department of Computer Science HongKong Hong Kong

The traditional polysomnography (PSG) examination for Obstructive Sleep Apnea (OSA) diagnosis needs to measure several signals, such as EEG, ECG, EMG, EOG and the oxygen level in blood, of a patient who may have to wear many sensors during sleep. After the PSG examination, the Apnea-Hypopnea Index (AHI) is calculated based on the measured data to evaluate the severity of apnea and hypopnea for the patient. This process is obviously complicated and inconvenient. In this paper, we propose an AI-based framework, called RAre Pattern Identification and DEtection for Sleep-stage Transitions (RAPIDEST), to detect OSA based on the sequence of sleep stages from which a novel rarity score is defined to capture the unusualness of the sequence of sleep stages. More importantly, under this framework, we only need EEG signals, thus significantly simplifying the signal collection process and reducing the complexity of the severity determination of apnea and hypopnea. We have conducted extensive experiments to verify the relationship between the rarity score and AHI and demonstrate the effectiveness of our proposed approach. © 2001-2011 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Integrated Sensing and Communications for Statistical-QoS Provisioning Over 6G M-MIMO Mobile Networks Using FBC

Integrated Sensing and Communications for Statistical-QoS Pr...

引用

IEEE International Conference on Communications (ICC)

作者： Xi Zhang Qixuan Zhu H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University TX USA Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Since the 6G mobile wireless networks require the high-performances on both channel state estimations and information transmissions, the technique of integrated sensing and communication (ISAC) has attracted considerable research attention due to its ability to sense and communicate by sharing the same frequency band and hardware. However, how to jointly optimize the sensing and communication functions of the ISAC to support the 6G traffic transmissions over a time-varying wireless fading channel has imposed many new challenges not encountered before. To conquer these difficulties, in this paper we propose the ISAC scheme to jointly sense the channel state and transmit the wireless-streaming data using massive multiple-input and multiple-output (massive MIMO) communications over the Rician fading channel. First, we establish the system models for the ISAC scheme under the Rician fading wireless channel and the channel state estimation scheme using the radar sensing feedback. Second, we define the channel state estimation distortion and the capacity-distortion function of a massive MIMO channel to jointly measure the performances of sensing and communication in our ISAC scheme. Third, we integrate the capacity-distortion function with the finite blocklength coding (FBC) scheme by developing the concept of the ISAC-based E-effective capacity to implement the statistical delay and error-rate bounded provisioning for supporting the 6G traffic under our ISAC scheme. Finally, we use numerical analyses to validate and evaluate our proposed ISAC scheme with massive MIMO in the non-asymptotic regime.

关键词： 6G mobile communication Wireless sensor networks Channel estimation Rician channels Massive MIMO Radar Quality of service

来源：评论

学校读者我要写书评

暂无评论

An Efficient Classification of Cassava Leaf Disease using VGG 16

An Efficient Classification of Cassava Leaf Disease using VG...

引用

2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Soujanya, A. Cherukuvada, Srikanth Murugan, V. Ramya, Singaraju Agalya, K. Gayathri, S. Ibrahimpatnam India School of Computing SRM Institute of Science and Technology Department of Networking and Communications Kattankulathur Chennai India CARE College of Engineering Department of Artificial Intelligence and Data Science Thayanur Trichy India SRM Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur Chennai India Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India K. Ramakrishnan College of Technology Department of Computer Science and Engineering Samayapuram Trichy India

ISBN: (纸本)9798350319200

Cassava is an essential food item in the tropics, it may origin enormous productivity decreases in cassava, leading to significant financial losses and a shortage of basic foods. Small-scale farmers grow the essential food and nutrition crop cassava because it can withstand harsh conditions. In many African nations, it provides a substantial source of carbohydrates. Leaf infections can occasionally harm cassava crops, limiting total productivity and farmers' income. In this study, Pre trained models are utilized for the determination of disease identification and classification on plant leaf issues. VGG 16 has been put into use, and its performance has been examined. An exploratory study is carried out using an online Cassava image collection, which contains pictures of Cassava leaves afflicted with five different disease categories. The vgg16 classifier that was suggested surpasses its competitors greatly and achieves an accuracy of 97.58%. The results of the test demonstrate that improving classification performance by using a database of images that is well balanced is possible. © 2023 IEEE.

关键词： Classification CNN Deep learning Transfer learning VGG16

来源：评论

学校读者我要写书评

暂无评论

1 Lyapunov Stability Analysis for Controlling UAV Trajectory Over 6G Wireless Networks

1 Lyapunov Stability Analysis for Controlling UAV Trajectory...

引用

2022 IEEE Military Communications Conference, MILCOM 2022

作者： Zhang, Xi Zhu, Qixuan Texas A&m University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States

ISBN: (纸本)9781665485340

With the commercial realization of the fifth generation (5G) wireless networks, the development of the sixth generation (6G) wireless networks has attracted considerable research attention. To meet the requirement of providing ubiquitous coverage, unmanned aerial vehicle (UAV) plays the key role in extending the line-of-sight area, and thus, has been proposed as a promising candidate technique in 6G wireless networks However, how to design an optimal UAV trajectory when it is moving and communicating with a base station or a mobile user in the network and how to guarantee the stability of the UAV's trajectory remain open problems. To address these issues, in this paper we design an optimal UAV trajectory, obtain the expression of the UAV's trajectory error, and propose a stability analysis mechanism to show that the UAV trajectory error is globally and asymptotically stable. First, we design the UAV optimal trajectory to maximize the communication performance while minimizing the energy consumption. Then, we derive a closed-form expression for the UAV trajectory in the transient state, which results in major trajectory errors, including the critical damping, underdamping, and overdamping. Third, we employ the control Lyapunov function to show that our developed UAV trajectory error correction scheme is globally and asymptotically stable under the feedback control law. Finally, we use numerical analyses to validate and evaluate our proposed UAV trajectory error control scheme. © 2022 IEEE.

关键词： Wireless networks

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous Face Recognition Algorithm: Convolution Neural Network Approach 5

Heterogeneous Face Recognition Algorithm: Convolution Neural...

引用

5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Sujatha, E. Manickam, M. Ani Minisha, R. Rekha, K.S. Indumathy, T. Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computing Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Chennai India Vel Tech Multi Tech Dr. Rr and Dr Sr Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu India Department of Medical Electronics Tamil Nadu Chennai India

ISBN: (纸本)9798350385649

Heterogeneous face recognition, also known as HFR, is an approach to facial recognition that attempts to match facial pictures that have been gathered through a variety of sensory modalities. HFR is primarily used for forensics, network security, and all commercial applications. The heterogeneous face recognition (HFR) algorithm is robust in handling challenges that exist in conventional face recognition. This is since heterogeneous face images display an enormous amount of intra- class variation, and it does not support hybrid modality of face images. This study provides a unique technique to transfer learning as a means of mastering invariant facial feature characteristics in visual (VIS) face pictures. A wrapping procedure combines end to end connections of two components for deep network. A discriminator has the details of fine-grained data for improving the quality of image which depends on wavelets. The system is made up of two different modules: one deals with face recognition, while the other determines a person's gender. It analysis about the characteristics of gender from the image using Convolutional Neural Networks that have been pre-trained. To train CNN in the face recognition module, in particular, the use of the open-source datasets Labelled Faces within the Wild, YouTube Face, and VGGFace2 results in an improvement in accuracy. Deep learning techniques and a substantial number of photographic examples of people's faces are what make it feasible for the proposed recognition to function so admirably. The problem of studying recognition remains challenging due to the limited size of the sample and the information gap between the senses. © 2024 IEEE.

关键词： Face recognition

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：