检索结果-内蒙古大学图书馆

FSCIL-EACA: Few-Shot Class-Incremental Learning network Based on Embedding Augmentation and Classifier Adaptation for Image Classification

引用

Chinese Journal of Electronics 2024年第1期33卷 139-152页

作者： Ruru ZHANG Haihong E Meina SONG School of Computer Science Beijing University of Posts and Telecommunications Education Department Information Network Engineering Research Center Beijing University of Posts and Telecommunications

The ability to learn incrementally is critical to the long-term operation of AI systems. Benefiting from the power of few-shot class-incremental learning(FSCIL), deep learning models can continuously recognize new classes with only a few samples. The difficulty is that limited instances of new classes will lead to overfitting and exacerbate the catastrophic forgetting of the old classes. Most previous works alleviate the above problems by imposing strong constraints on the model structure or parameters, but ignoring embedding network transferability and classifier adaptation(CA), failing to guarantee the efficient utilization of visual features and establishing relationships between old and new classes. In this paper, we propose a simple and novel approach from two perspectives: embedding bias and classifier bias. The method learns an embedding augmented(EA) network with cross-class transfer and class-specific discriminative abilities based on self-supervised learning and modulated attention to alleviate embedding bias. Based on the adaptive incremental classifier learning scheme to realize incremental learning capability,guiding the adaptive update of prototypes and feature embeddings to alleviate classifier bias. We conduct extensive experiments on two popular natural image datasets and two medical datasets. The experiments show that our method is significantly better than the baseline and achieves state-of-the-art results.

关键词： Few-shot class-incremental learning Embedding augmentation Classifier adaptation Image classification

来源：评论

学校读者我要写书评

暂无评论

Entropy-Bottleneck-Based Privacy Protection Mechanism for Semantic Communication

引用

computers, Materials & Continua 2025年第5期83卷 2971-2988页

作者： Kaiyang Han Xiaoqiang Jia Yangfei Lin Tsutomu Yoshinaga Yalong Li Jiale Wu School of Information Engineering Inner Mongolia University of TechnologyHohhot010051China Department of Computer and Network Engineering University of Electro-CommunicationsChofuTokyo1828585Japan

With the rapid development of artificial intelligence and the Internet of Things,along with the growing demand for privacy-preserving transmission,the need for efficient and secure communication systems has become increasingly *** communication methods transmit data at the bit level without considering its semantic significance,leading to redundant transmission overhead and reduced *** communication addresses this issue by extracting and transmitting only the mostmeaningful semantic information,thereby improving bandwidth ***,despite reducing the volume of data,it remains vulnerable to privacy risks,as semantic features may still expose sensitive *** address this,we propose an entropy-bottleneck-based privacy protection mechanism for semantic *** approach uses semantic segmentation to partition images into regions of interest(ROI)and regions of non-interest(RONI)based on the receiver’s needs,enabling differentiated semantic *** focusing transmission on ROIs,bandwidth usage is optimized,and non-essential data is *** entropy bottleneck model probabilistically encodes the semantic information into a compact bit stream,reducing correlation between the transmitted content and the original data,thus enhancing privacy *** proposed framework is systematically evaluated in terms of compression efficiency,semantic fidelity,and privacy *** comparative experiments with traditional and state-of-the-art methods,we demonstrate that the approach significantly reduces data transmission,maintains the quality of semantically important regions,and ensures robust privacy protection.

关键词： Semantic communication privacy protection semantic segmentation entropy-based compression

来源：评论

学校读者我要写书评

暂无评论

Distribution-Based Time-Varying Ensemble Scientific Data Reduction for Uncertainty Visualization and Analysis

引用

Journal of information Science and engineering 2024年第2期40卷 397-419页

作者： Lin, Zhi-Rong Hsiao, An-Lung Li, Guan Wang, Ko-Chih Department of Computer Science and Information Engineering National Taiwan Normal University Taipei106 Taiwan Computer Network Information Center Chinese Academy of Sciences Beijing100083 China

Scientists often study physical phenomena using computer simulation models. The same simulation can generate different datasets because of different input parameter configurations or internal random variables. Therefore, each grid point is represented by multiple data values from simulation runs, and we call this type of data ensemble dataset. To gain insight into the physical phenomenon, scientists often have to visualize and analyze the ensemble datasets with uncertainty. Distribution-based data representation is a popular approach to handling the ensemble dataset and supporting uncertainty visualization. However, storing a time-varying ensemble dataset needs hundreds or even thousands of times storage size. Given the size of the time-varying ensemble dataset, it is natural to develop storage-reduced data representation to facilitate the time-varying ensemble data exploration. We propose a novel data representation to compactly represent the time-varying scientific data for uncertainty visualization and analysis. Our approach decouples data on the temporal domain into two types of distributions and stores. One distribution summarizes the data values on the temporal domain, and the other distribution describes the occurrence probability of a data value on the temporal domain. Our approach can provide time-varying ensemble scientific data analysis with uncertainty quantification and detailed temporal feature evolution with less storage requirement. © 2024 Institute of information Science. All rights reserved.

关键词： Probability distributions

来源：评论

学校读者我要写书评

暂无评论

Effective Controller Placement in Software-Defined Internet-of-Things Leveraging Deep Q-Learning (DQL)

引用

computers, Materials & Continua 2024年第12期81卷 4015-4032页

作者： Jehad Ali Mohammed J.F.Alenazi Department of AI Convergence Network Ajou UniversitySuwon16499Republic of Korea Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11362Saudi Arabia

The controller is a main component in the Software-Defined networking(SDN)framework,which plays a significant role in enabling programmability and orchestration for 5G and next-generation *** SDN,frequent communication occurs between network switches and the controller,which manages and directs traffic *** the controller is not strategically placed within the network,this communication can experience increased delays,negatively affecting network ***,an improperly placed controller can lead to higher end-to-end(E2E)delay,as switches must traverse more hops or encounter greater propagation delays when communicating with the *** paper introduces a novel approach using Deep Q-Learning(DQL)to dynamically place controllers in Software-Defined Internet of Things(SD-IoT)environments,with the goal of minimizing E2E delay between switches and controllers.E2E delay,a crucial metric for network performance,is influenced by two key factors:hop count,which measures the number of network nodes data must traverse,and propagation delay,which accounts for the physical distance between *** approach models the controller placement problem as a Markov Decision Process(MDP).In this model,the network configuration at any given time is represented as a“state,”while“actions”correspond to potential decisions regarding the placement of controllers or the reassignment of switches to *** a Deep Q-network(DQN)to approximate the Q-function,the system learns the optimal controller placement by maximizing the cumulative reward,which is defined as the negative of the E2E ***,the lower the delay,the higher the reward the system receives,enabling it to continuously improve its controller placement *** experimental results show that our DQL-based method significantly reduces E2E delay when compared to traditional benchmark placement *** dynamically learning from the network’s real-time conditions,the prop

关键词： Software-defined networking deep Q-learning controller placement quality of service

来源：评论

学校读者我要写书评

暂无评论

AI-enabled dental caries detection using transfer learning and gradient-based class activation mapping

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第7期15卷 3009-3033页

作者： Inani, Hardik Mehta, Veerangi Bhavsar, Drashti Gupta, Rajeev Kumar Jain, Arti Akhtar, Zahid Department of Computer Science and Engineering Pandit Deendayal Energy University Gujarat Gandhinagar India Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Uttar Pradesh Noida India Department of Network and Computer Security State University of New York Polytechnic Institute NY United States

Dental caries detection holds the key to unlocking brighter smiles and healthier lives by identifying one of the most common oral health issues early on. This vital topic sheds light on innovative ways to combat tooth decay, empowering individuals to take control of their oral health and maintain radiant smiles. This research paper delves into the realm of transfer learning techniques, aiming to elevate the precision and efficacy of dental caries diagnosis. Utilizing Keras ImageDataGenerator, a rich and balanced dataset is crafted by augmenting teeth images from the Kaggle teeth dataset. Five cutting-edge pre-trained architectures are harnessed in the transfer learning approach: EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50, with each model, initialized using ImageNet weights and tailored top layers. A comprehensive set of evaluation metrics, encompassing accuracy, precision, recall, F1-score, and false negative rates are employed to gauge the performance of these architectures. The findings unveil the unique advantages and drawbacks of each model, illuminating the path to an optimal choice for dental caries detection using Grad-CAM (Gradient-weighted Class Activation Mapping). The testing accuracies achieved by EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50 models stand at 95.89%, 96.58%, 93.15%, 93.15%, and 94.18%, respectively. The Training accuracies stood at 100%, 99.91%, 100%, 100% and 100%, meanwhile on validation we achieved 97.63%, 96.68%, 98.82%, 96.68%, and 100% accuracies for EfficientNetV2B3, VGG19, InceptionResNetV2, Xception, and ResNet50 models respectively. Capitalizing on transfer learning and juxtaposing diverse pre-trained architectures, this research paper paves the way for substantial advancements in dental diagnostic capabilities, culminating in enhanced patient outcomes and superior oral health. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Chemical activation

来源：评论

学校读者我要写书评

暂无评论

Towards robust and efficient intrusion detection in IoMT: a deep learning approach addressing data leakage and enhancing model generalizability

引用

Multimedia Tools and Applications 2024年 1-20页

作者： Bouke, Mohamed Aly El Atigh, Hayate Abdullah, Azizol Department of Communication Technology and Network Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang43400 Malaysia Departement of Computer Engineering Faculty of Computer Engineering Bandirma Onyedi Eylul University Balikesir10200 Turkey

The Internet of Medical Things (IoMT) brings advanced patient monitoring and predictive analytics to healthcare but also raises cybersecurity and data privacy issues. This paper introduces a deep-learning model for IoMT intrusion detection, utilizing the WUSTL EHMS 2020 dataset, which focuses on cyber threats like man-in-the-middle attacks and data injection. Our sequential model, trained with TensorFlow, surpasses traditional predictive accuracy and efficiency methods. It achieves 99% accuracy with reduced loss and excels in precision, recall, F1 Score, and ROC AUC. The model uses 25 key features from 45, preventing overfitting and addressing data leakage in preprocessing. These steps ensure the model's reliability for IoMT cybersecurity, demonstrating its effectiveness in real-world scenarios. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Signal Detection for Quadrature Spatial Modulation System

引用

China Communications 2024年第10期21卷 78-85页

作者： Shu Dingyun Peng Yuyang Yue Ming Fawaz AL-Hazemi Mohammad Meraj Mirza School of Computer Science and Engineering Macao University of Science and TechnologyMacaoChina Department of Computer and Network Engineering University of JeddahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. In QSM, the traditional signal detection methods sometimes are unable to meet the actual requirement of low complexity of the system. Therefore, this paper proposes a signal detection scheme for QSM systems using deep learning to solve the complexity problem. Results from the simulations show that the bit error rate performance of the proposed deep learning-based detector is better than that of the zero-forcing(ZF) and minimum mean square error(MMSE) detectors, and similar to the maximum likelihood(ML) detector. Moreover, the proposed method requires less processing time than ZF, MMSE,and ML.

关键词： bit error rate complexity deep learning quadrature spatial modulation

来源：评论

学校读者我要写书评

暂无评论

ENHANCING HEALTH CARE THROUGH REMOTE SERVICES AND INTERACTIVE TECHNOLOGIES 9

ENHANCING HEALTH CARE THROUGH REMOTE SERVICES AND INTERACTIV...

引用

9th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2024, the 10th International Conference on Connected Smart Cities, CSC 2024 and the 16th International Conference on e-Health, EH 2024, Part of the 18th Multi Conference on computer Science and information Systems 2024, MCCSIS 2024

作者： Lu, Ssu-Hsuan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan Taiwan

ISBN: (纸本)9789898704597

With the aging population, health issues have become a significant challenge for society. The increasing demand for remote medical services stems from changing interests in reducing healthcare costs and the sudden outbreak of COVID-19 globally. As the Internet of Things (IoT) and cloud technology advance rapidly worldwide, this trend has driven the digital transformation of biotechnology and pharmaceutical-related industries. Health care is shifting from a focus on medical institutions to a decentralized approach, emphasizing care facilities and home-based services. However, remote medical care brings about certain challenges, such as limited appointment availability due to network constraints, concerns about internet security, data encryption, privacy issues, and lack of awareness among people in remote areas. With the continuous development and widespread adoption of technology, smart home systems have become an integral part of modern life. In this project, the system emphasizes interaction with the elderly and utilizes the multifunctionality of touch screens. It provides various features through a simple and user-friendly interface, including health monitoring, outpatient services, life assistance, and social interaction functions. In the future, the system can incorporate more interactive features for the elderly, such as mini-games to enhance cognitive abilities, hand-eye coordination, or rehabilitation training. © 2024 Big Data Analytics, Data Mining and Computational Intelligence. All Rights Reserved.

关键词： Touch screens

来源：评论

学校读者我要写书评

暂无评论

Image Recognition Technology Supported Environment Monitoring Smart Fan 7

Image Recognition Technology Supported Environment Monitorin...

引用

7th IEEE Eurasian Conference on Educational Innovation, ECEI 2024

作者： Yang, Sheng-Yuan Lee, Hsiu-Chia Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan Taiwan

ISBN: (纸本)9798350307207

Owing to the development of the Internet of Things (IoT), smart electrical appliances bring convenience to life. However, smart home appliances are too cumbersome as their interface operations are mostly not intuitive with less practicability than expected. Taiwan has an island climate, and the summer weather is scorching. An easy-to-use and practical electric fan is indispensable for cooling off the heat, which is the research object of this study to make users feel comfortable. In this study, image recognition technology was introduced. The user turns on the fan manually or through the mobile APP, and selects the tracking mode through the mode function. The camera with the fan detects the user's position and then starts to track the user. The device is equipped with a smoke sensor and a camera to monitor the user's home. The fan proves the feasibility of the conceptual architecture. © 2024 IEEE.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Developing an Esports Assistant System for First Person Shooting Game Based on Multimodal Learning 14th

Developing an Esports Assistant System for First Person Shoo...

引用

14th International Conference on Frontier Computing, FC 2024

作者： Chiu, Wei-Hsiang Hung, Jason C. Ma, Hao-Shang Huang, Chun-Hong Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (纸本)9789819623945

We plan to develop a specialized training system to enhance the competitive skills of players in the first-person shooter game "Valorant", aiming to improve their abilities and tactical understanding within the game. We will adopt a multimodal image-text fusion technique to enhance the model’s learning of sample similarity. Specifically, we will use the cross-entropy function to maximize the diagonal values of the similarity matrix, thereby capturing the features of similar samples and reducing the similarity between dissimilar samples. Through this process, we ensure that the model can map the same entity across different modalities into similar embedding representations, while distinguishing unrelated samples. Our goal is to find a way of embedding representation during the learning process that enables the model to better understand and represent multimodal data. We will utilize the YOLOv7 model for object detection to identify destructible skills. Based on the results of object detection, we will generate relevant textual descriptions for each object. This will enable novice players to quickly understand the function of diverse and complex skills and take appropriate actions when encountering them. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Object detection

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：