检索结果-内蒙古大学图书馆

IEEE Networking Letters 2024年第2期6卷 148-151页

作者： Yuan, Qingjun Niu, Weina Wang, Yongjuan Gou, Gaopeng Lu, Bin Henan Key Laboratory of Network Cryptography Technology Zhengzhou450001 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China

To train robust malicious traffic identification models under noisy labeled datasets, a number of learning with noise labels approaches have been introduced, among which parallel training methods have been proved to be effective. Parallel training methods tend to select samples with disagreement to mitigate the risk of self-control degradation. However, it also introduces noisy knowledge into training. In this letter, we try to avoid introducing noisy knowledge by enhancing the consistency of the representations of parallel networks. Meanwhile, the two networks are heterogeneous and introduce information from different modalities, thus mitigating the risk of self-control degradation from multiple perspectives. © 2019 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Developing a Convolutional Neural Model for Segmentation of Medical Images 1

Developing a Convolutional Neural Model for Segmentation of ...

引用

1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Arunachalam, M. Kumar, P. Mohan Selvam, L. Kumar, S. Senthil Arunkumar, B. Sri Krishna College of Engineering and Technology Department of Information Technology Coimbatore India Hindusthan Institute of Technology & Sciences Department of Computer Science and Engineering Chennai India Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India Sethu Institute of Technology Department of Computer Science and Engineering Kariapatti India

ISBN: (纸本)9798350359756

Medical image segmentation is a new biomedical image processing method that has made a significant contribution to sustainable health care. It has now become a major study area in the realm of computer vision research. Medical image processing based on deep convolutional neural networks has become a research hotspot due to the fast development of deep learning techniques. An additional cascade component is included to the architecture in this article to better replicate spatial closure tags' direct dependences. It is also utilised for post-segmentation processing, resolving the conflict between classification performance and network intensity and number of mixing times in a typical convolutional net. Numerous state-of-the-art deep recognition models, and a multi-atlas segmentation methodology, are outperformed by our methodology. © 2023 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Memory-enhanced text style transfer with dynamic style learning and calibration

引用

science China(Information sciences) 2024年第4期67卷 181-196页

作者： Fuqiang LIN Yiping SONG Zhiliang TIAN Wangqun CHEN Diwen DONG Bo LIU College of Computer Science and Technology National University of Defense Technology Department of Computer Science and Engineering The Hong Kong University of Science and Technology Strategic Assessments and Consultation Institute Academy of Military Sciences

Text style transfer aims to rephrase a sentence to match the desired style while retaining the original content. As a controllable text generation task, mainstream approaches use content-independent style embedding as control variables to guide stylistic generation. Nonetheless, stylistic properties are contextsensitive even under the same style. For example, “delicious” and “helpful” convey positive sentiments,although they are more likely to describe food and people, respectively. Therefore, desired style signals must vary with the content. To this end, we propose a memory-enhanced transfer method, which learns fine-grained style representation concerning content to assist transfer. Rather than employing static style embedding or latent variables, our method abstracts linguistic characteristics from training corpora and memorizes subdivided content with the corresponding style representations. The style signal is dynamically retrieved from memory using the content as a query, providing a more expressive and flexible latent style space. To address the imbalance between quantity and quality in different content, we further introduce a calibration method to augment memory construction by modeling the relationship between candidate *** results obtained using three benchmark datasets confirm the superior performance of our model compared to competitive approaches. The evaluation metrics and case study also indicate that our model can generate diverse stylistic phrases matching context.

关键词： style transfer memory-enhanced method text generation deep learning text representation

来源：评论

学校读者我要写书评

暂无评论

An Efficient Depth Estimation Technique for Visual Perception

An Efficient Depth Estimation Technique for Visual Perceptio...

引用

2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Deepa Shubham, A. Shetty, Bhuvan Aravind Dhanush Kumar, Archana Praveen Department of Information Science and Engineering Karnataka Nitte India Manipal Institute of Technology Manipal Academy of Higher Education Department of Computer Science and Engineering Karnataka Manipal576104 India

ISBN: (纸本)9798350388602

In the realm of computer vision and 3D reconstruction, the accurate conversion of images into depth maps is crucial. This paper focuses on depth estimation techniques to assess their accuracy and reliability in generating depth maps from 2D images. Subsequently, the depth maps were transformed into 3D representations using Open3D in Python, enabling the visualization and reconstruction of three-dimensional scenes. Despite challenges such as noise and artifacts, the reconstruction process yielded promising results, highlighting the potential of image-based 3D reconstruction techniques. This study contributes to the advancement of computer vision technologies by providing insights into improving depth estimation accuracy and enhancing the fidelity of reconstructed 3D models. Additionally, the successful reconstruction of 3D scenes underscores the practical utility of image-based 3D reconstruction methodologies in various domains, including robotics, augmented reality, and autonomous driving. © 2024 IEEE.

关键词： Machine vision

来源：评论

学校读者我要写书评

暂无评论

Intelligent Recognition of Optical Modulation Formats in Dynamic Communication Networks 1

Intelligent Recognition of Optical Modulation Formats in Dyn...

引用

1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Gnanakumar, D. Anusooya, V. Muthupradeepa, R. Gobalakrishnan, S. Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil India Srm Institute of Science and Technology Department of Electronics and Communication Engineering Kattankulathur India Thandalam India

ISBN: (纸本)9798350352931

Machine learning-based optical modulation format recognition is essential for dynamic optical networks. Convolutional Neural Networks (CNNs) can analyze signal space diagrams directly from raw data. Specifically, CNNs excel in image classification due to their ability to extract features and learn autonomously. In this study, signal space diagrams for various modulation formats (BPSK, QPSK, 8-QAM, 16-QAM, 32-QAM, and 64-QAM) are generated using an electrical constellation visualizer in Optisystem software, with the Optical Signal-to-Noise Ratio (OSNR) varying from 10 to 40 dB and the noise figure ranging from 5 to 25 dB. The proposed VGG-16 CNN architecture achieves 100% accuracy in modulation format recognition (MFR) for all six formats, utilizing minimal training data and fewer epochs. This approach can significantly enhance next-generation dynamic optical communication networks by enabling automatic detection and recognition of modulation formats. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

LPCC Based Music Genrefication Using Hybrid Computational Model 7

LPCC Based Music Genrefication Using Hybrid Computational Mo...

引用

2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Sul, Astha Sarda, Harshit Billa, Aishwarya Mishra, Tusar Kanti School of Computer Science and Engineering Vellore Institute of Technology Vellore India Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Dept. of Computer Science and Engineering Manipal India

ISBN: (纸本)9798350304268

This work deals with spontaneous music genrefication through computational models which in the recent times has been gaining importance rapidly. Through these hybrid computational models implemented users get an enhanced level of satisfaction when their choice of music files genre with least latency is gained. The paper includes the use of LPCC attributes to obtain the features of the music files along with robust classification models such as neural networks. For this purpose, one thousand audio files are taken as the sample set. The input audio file is pre-processed and suitable LPCC features are computed and stored into final vector. The pool of vectors of numerous audio samples are finally utilized to train a neural model. The proposed work trains the model for ten very distinct categories of music such as hip-hop, jazz, metal, pop, blues, classical, country, disco, reggae, and rock. Further, a comparison is also made between all the classifiers such as SVM, ANN and random forest (RF). Comparatively the best accuracy rate of 85.53\% has been achieved for the proposed work that validates its effectiveness. © 2023 IEEE.

关键词： ANN gtzan dataset LPCC Music Genre

来源：评论

学校读者我要写书评

暂无评论

Poster Abstract: On the Accuracy and Robustness of Large Language Models in Chinese Industrial Scenarios 23

Poster Abstract: On the Accuracy and Robustness of Large Lan...

引用

23rd ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2024

作者： Li, Zongjie Qiu, Wenying Ma, Pingchuan Li, Yichen Li, You He, Sijia Jiang, Baozheng Wang, Shuai Gu, Weixi Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong Hong Kong China Academy of Industrial Internet Beijing China

ISBN: (纸本)9798350362015

Recent studies have demonstrated that large language models (LLMs) exhibit exceptional performance across various natural language processing tasks, rivaling or even exceeding human competencies in certain areas [1] - [5]. Typically, LLMs undergo pre-training on extensive text corpora, usually using billions of tokens to develop a foundational model. To better align LLMs with human preferences and directives or to fulfill specific application needs, methods such as supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and direct preference optimization (DPO) have been introduced and demonstrated to be effective. These advancements facilitate more intuitive and efficient human-AI interactions. However, the substantial resource requirements throughout the training process pose challenges for individual users and smaller organizations. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

引用

Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye University34010 IstanbulTurkey

Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm ***,little attention has been paid to the ambiguous weather information implicit in AEFS *** this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by ***,a time series dataset is created in the time domain using AEFS *** AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the ***,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF ***,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space ***,the rationality and reliability of the proposed method are verified by combining radar charts and expert *** results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first *** detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field(AEF) Thunderstorm Fuzzy C-means(FCM) Attribute

来源：评论

学校读者我要写书评

暂无评论

Secure Communication in Resource-Constrained IoT Environments using MQTT Protocol: A Review 3

Secure Communication in Resource-Constrained IoT Environment...

引用

3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Kaganurmath, Sharadadevi Cholli, Nagaraj G. Department of Computer Science Engineering Global Academy of Technology Bengaluru Visvesvaraya Technological University India Department of Information Science Engineering RV College of Engineering Bengaluru Visvesvaraya Technological University India

ISBN: (纸本)9798331532420

The Internet of Things (IoT) has revolutionized our lives by connecting a vast array of devices. The Message Queuing Telemetry Transport (MQTT) protocol plays a crucial role in enabling efficient communication between these devices. However, the resource-constrained nature of many IoT devices presents significant security challenges. This research review comprehensively addresses the security management of resource-constrained IoT devices utilizing the MQTT protocol. It explores the unique security threats faced by IoT devices, including those related to computation, memory, and energy constraints. The paper examines various security measures applicable to MQTT, such as authentication, encryption, and access control mechanisms, tailored to the specific needs of resource-constrained devices. This comprehensive review provides valuable insights into the security challenges and solutions for IoT devices utilizing the MQTT protocol, guiding researchers, developers, and stakeholders in enhancing the security and reliability of IoT ecosystems. © 2024 IEEE.

关键词： Telemetering

来源：评论

学校读者我要写书评

暂无评论

Solar Observation with the Fourier Transform *** Results of Solar Spectrum near the CO 4.66μm and Mg I 12.32μm

引用

Research in Astronomy and Astrophysics 2023年第12期23卷 128-137页

作者： Xianyong Bai Zhiwei Feng Zhiyong Zhang Yuanyong Deng Xiaoming Zhu Kaifan Ji Song Feng Xiao Yang Yongliang Song National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 101408China Yunnan Observatories Chinese Academy of SciencesKunming 650011China Faculty of Information Engineering and Automation/Yunnan Key Laboratory of Computer Technology Application Kunming University of Science and TechnologyKunming 650500China

An infrared solar spectrum observed by ground-based telescopes is seriously affected by the background radiation both from the telescope and sky,relative to the visible *** accuracy is also influenced by the spectral resolution of the Fourier transform *** the paper,we developed a CO_(2)gas cell and installed it in the sample compartment to calibrate the spectral resolution of the Bruker IFS-125HR at infrared *** measured spectral resolution is 0.00342±0.00086 cm^(-1)and 0.0059±0.00024 cm^(-1)at the wavenumbers of798 cm^(-1)and 2136 cm^(-1),*** also updated a fully reflective sunlight feeding system to observe the solar spectrum near CO 4.66μm and Mg I 12.32μ*** quickly pointing the sunlight feeding system about1 degree away from the solar disk center,we are able to measure the background radiation from the telescope and the sky at Huairou Solar Observing *** removing the background radiation,our observed solar spectrum at CO 4.66μm is consistent with that from the National Solar *** Mg I 12.32μm working line selected by the Accurate Infrared Magnetic Field Measurements of the Sun(AIMS)project is also *** method is helpful not only for the spectral resolution calibration and background radiation correction of AIMS but also for other infrared astronomical telescopes.

关键词： Sun infrared-methods observational-instrumentation interferometers

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：