检索结果-内蒙古大学图书馆

28th International Conference on Optical Fiber Sensors, OFS 2023

作者： Li, Yujiao Yu, Kuanglu Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University Beijing100044 China

We design a semi-supervised model based on XM-ACAB for Φ-OTDR event classification. The accuracy for six types of events can reach up to 91.0% with a total of only 12 labeled samples in the experiment. © Optica ... 详细信息

ISBN: (纸本)9781957171302

关键词： Deep learning Erbium fibers Machine learning Neural networks Optical time domain reflectometry Single mode fibers

来源：评论

学校读者我要写书评

暂无评论

Research on ECG classification based on transfer learning

引用

The Journal of China Universities of Posts and Telecommunications 2022年第6期29卷 83-96页

作者： Jiang Fan Chen Jiajun Gao Youjun Sun Changyin Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and TelecommunicationsXi'an 710121China China Mobile System Integration Co. Ltd.Beijing 100052China China Mobile Xiong'an Information Communication Technology Co. Ltd.Beijing 100052China

Concerning current deep learning-based electrocardiograph(ECG) classification methods, there exists domain discrepancy between the data distributions of the training set and the test set in the inter-patient paradigm. To reduce the negative effect of domain discrepancy on the classification accuracy of ECG signals, this paper incorporates transfer learning into the ECG classification, which aims at applying the knowledge learned from the training set to the test set. Specifically, this paper first develops a deep domain adaptation network(DAN) for ECG classification based on the convolutional neural network(CNN). Then, the network is pre-trained with training set data obtained from the famous Massachusetts Institute of Technology-Beth Israel Hospital(MIT-BIH) ECG arrhythmia database. On this basis, by minimizing the multi-kernel maximum mean discrepancy(MK-MMD) between the data distributions of the training set and the test set, the pre-trained network is adjusted to learn transferable feature representations. Finally, with the low-density separation of unlabeled target data, the feature representations are more transferable. The extensive experimental results show that the proposed domain adaptation method has reached a 7.58% improvement in overall classification accuracy on the test set, and achieves competitive performance with other state-of-the-arts.

关键词： electrocardiograph(ECG)classification transfer learning domain adaptation convolutional neural network(CNN)

来源：评论

学校读者我要写书评

暂无评论

引用

8th International Congress on Edge Computing, EDGE 2024, Held as Part of the Services Conference Federation, SCF 2024

作者： Tian, Yun Wu, Bin Shi, Jiaoli Zhang, Caicai Xu, Du School of Computer and Big Data Science Jiujiang University Jiujiang332005 China Jiujiang Key Laboratory of Network and Information Security Jiujiang332005 China School of Modern Information Technology Zhejiang Polytechnic University of Mechanical and Electrical Engineering Hangzhou310053 China

ISBN: (纸本)9783031770685

The development of cloud computing and the widespread application of cloud services have made outsourcing services more convenient. The need for individuals and businesses to store and manipulate the graph data they generate is growing rapidly. The unreliability and insecurity of cloud servers make outsourcing graph data a great risk of information leakage. To effectively protect data security, encrypting outsourced data is a useful method. The adjacent vertex query is a very commonly used and fundamental operation, and similarity search is a widely used and powerful tool to improve the scope and functionality of queries. After outsourcing encrypted sparse graph data to cloud servers, it becomes very inconvenient to use and manipulate the data. In this work, we present a scheme to realize the adjacent vertex query supporting similarity search on sparse graph data in cloud environment (SSAQ), which also protects the security of the information. This work uses edit distance and the searchable encryption principle to construct query index, and next implement the similar adjacent vertex query on cloud server. This work provides a formal security analysis, and also gives the experimental comparison and analysis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： information leakage

来源：评论

学校读者我要写书评

暂无评论

Improving Scene Text Image Super-resolution via Dual Prior Modulation network

arXiv

引用

arXiv 2023年

作者： Zhu, Shipeng Zhao, Zuoyan Fang, Pengfei Xue, Hui School of Computer Science and Engineering Southeast University Nanjing210096 China MOE Key Laboratory of Computer Network and Information Integration Southeast University China

Scene text image super-resolution (STISR) aims to simultaneously increase the resolution and legibility of the text images, and the resulting images will significantly affect the performance of downstream tasks. Although numerous progress has been made, existing approaches raise two crucial issues: (1) They neglect the global structure of the text, which bounds the semantic determinism of the scene text. (2) The priors, e.g., text prior or stroke prior, employed in existing works, are extracted from pre-trained text recognizers. That said, such priors suffer from the domain gap including low resolution and blurriness caused by poor imaging conditions, leading to incorrect guidance. Our work addresses these gaps and proposes a plug-and-play module dubbed Dual Prior Modulation network (DPMN), which leverages dual image-level priors to bring performance gain over existing approaches. Specifically, two types of prior-guided refinement modules, each using the text mask or graphic recognition result of the low-quality SR image from the preceding layer, are designed to improve the structural clarity and semantic accuracy of the text, respectively. The following attention mechanism hence modulates two quality-enhanced images to attain a superior SR result. Extensive experiments validate that our method improves the image quality and boosts the performance of downstream tasks over five typical approaches on the benchmark. Substantial visualizations and ablation studies demonstrate the advantages of the proposed DPMN. Code is available at: https://***/jdfxzzy/DPMN. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Proposal Feature Learning Using Proposal Relations for Weakly Supervised Object Detection

Proposal Feature Learning Using Proposal Relations for Weakl...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhaofei Wang Weijia Zhang Min-Ling Zhang School of Computer Science and Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China School of Information and Physical Sciences The University of Newcastle NSW Australia

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Weakly Supervised Object Detection (WSOD) trains detectors using only image-level annotations. Most existing WSOD models are based on pre-computed proposals and do not fully explore the relations of proposals. In this work, we address this limitation by proposing two approaches of Proposal Feature Learning for WSOD (PFL-WSOD), which effectively capture intra-proposal relations and inter-proposal relations respectively, thus improving proposal representation. To extract intra-proposal relations, we propose to utilize Self-Attention on Single Proposal for capturing relations inside each proposal. For inter-proposal relations, we propose Salient Region Banks by capturing a unique type of inter-proposal relation called deep inclusion, which significantly improves proposal representation when used in synergy with contrastive learning. Experimental results on benchmarks demonstrate the effectiveness of our methods.

关键词： Representation learning Annotations Object detection Contrastive learning Detectors Benchmark testing Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Conditional selection with CNN augmented transformer for multimodal affective analysis

引用

CAAI Transactions on Intelligence Technology 2024年第4期9卷 917-931页

作者： Jianwen Wang Shiping Wang Shunxin Xiao Renjie Lin Mianxiong Dong Wenzhong Guo College of Computer and Data Science Fuzhou UniversityFuzhouChina College of Computer and Cyber Security Fujian Normal UniversityFuzhouChina Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhouChina Digital Fujian Institute of Big Data Security Technology Fujian Normal UniversityFuzhouChina Department of Sciences and Informatics Muroran Institute of TechnologyMuroranJapan

Attention mechanism has been a successful method for multimodal affective analysis in recent years. Despite the advances, several significant challenges remain in fusing language and its nonverbal context information. One is to generate sparse attention coefficients associated with acoustic and visual modalities, which helps locate critical emotional se-mantics. The other is fusing complementary cross‐modal representation to construct optimal salient feature combinations of multiple modalities. A Conditional Transformer Fusion network is proposed to handle these problems. Firstly, the authors equip the transformer module with CNN layers to enhance the detection of subtle signal patterns in nonverbal sequences. Secondly, sentiment words are utilised as context conditions to guide the computation of cross‐modal attention. As a result, the located nonverbal fea-tures are not only salient but also complementary to sentiment words directly. Experi-mental results show that the authors’ method achieves state‐of‐the‐art performance on several multimodal affective analysis datasets.

关键词： affective computing data fusion information fusion multimodal approaches

来源：评论

学校读者我要写书评

暂无评论

KGAPG: Knowledge-Aware Neural Group Representation Learning for Attentive Prescription Generation of Traditional Chinese Medicine

KGAPG: Knowledge-Aware Neural Group Representation Learning ...

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Li, Shuchen Wang, Wei He, Jieyue MOE Southeast University Key Lab of Computer Network Information Integration Nanjing China

ISBN: (纸本)9781665401265

Prescriptions play an essential role in the process of Traditional Chinese Medicine (TCM) diagnosis and treatment. Prescription generation is to generate a set of herbs to treat the symptoms of a patient by analyzing the relationship between symptoms and herbs. Although there have been a couple of studies to generate prescriptions, they have ignored the implicit relationship between the different symptoms of the patients. In addition, abundant semantic information and interpretability of the knowledge graph can help to portray the complicated relationships between the various modules of TCM. Therefore, this paper proposes a Knowledge-Aware neural Group representation learning model for Attentive Prescription Generation of Traditional Chinese Medicine (KGAPG), which regards the prescription generation task as a group recommendation problem. More specifically, multiple symptoms of a patient are considered as a symptom group and the complicated semantic information between symptoms and herbs can be captured by the knowledge graph. The syndrome information of multiple symptoms which is summarized by a group aggregation method based on the attention mechanism is applied to simulate the actual process of TCM diagnosis and treatment. The experiment results demonstrate that KGAPG is effective on a TCM prescription benchmark dataset, and its evaluation indicators of Precision, Recall and NDCG exceed other state-of-the-art methods. © 2021 IEEE.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

A decouple-decomposition noise analysis model for closed-loop mode-localized tilt sensors

引用

Microsystems & Nanoengineering 2023年第6期9卷 297-307页

作者： Kunfeng Wang XingYin Xiong Zheng Wang Liangbo Ma BoWen Wang WuHao Yang Xiaorui Bie ZhiTian Li XuDong Zou The State Key Laboratory of Transducer Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos AngelesCAUSA Shangdong Key Laboratory of Low-altitude Airspace Surveillance Network Technology QiLu Aerospace Information Research InstituteJinanChina

The development of mode-localized sensors based on amplitude output metrics has attracted increasing attention in recent years due to the potential of such sensors for high sensitivity and ***-localization phenomena leverage the interaction between multiple coupled resonant modes to achieve enhanced performance,providing a promising solution to overcome the limitations of traditional sensing *** noise plays a key role in determining the resolution of mode-localized sensors,as the output metric is derived from the measured AR(amplitude ratio)within the weakly coupled resonator ***,the amplitude noise originating from the weakly coupled resonator's closed-loop circuit has not yet been fully *** paper presents a decouple-decomposition(DD)noise analysis model,which is applied to achieve high resolution in a mode-localized tilt sensor based on a weakly coupled resonator closed-loop *** DD noise model separates the weakly coupled resonators using the decoupling method considering the nonlinearity of the *** integrating the decoupled weakly coupled resonators,the model decomposes the weakly coupled resonator's closed-loop circuit into distinct paths for amplitude and phase noise *** DD noise model reveals noise effects at various circuit nodes and models the system noise in the closed-loop circuit of the weakly coupled ***/Simulink simulations verify the model's accuracy when compared to theoretical *** the optimal operating point,the mode-localized tilt sensor achieves an input-referred instability of 3.91×10^(-4°)and an input-referred AR of PSD of 2.01×10^(-4°)⁄√Hz using the closed-loop noise *** model is also applicable to other varieties of mode-localized sensors.

关键词： weakly couple overcome

来源：评论

学校读者我要写书评

暂无评论

Transmissive reconfigurable metasurface enabling independent control of active and passive modules through weak coupling

引用

Photonics Research 2024年第7期12卷 1449-1456页

作者： KUN XUE HENG WEI CILEI ZHANG YONGHAO ZHANG HAOLIANG SUN SHAOHUA DONG Peng Cheng Laboratory Shenzhen 518055China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore State Key Laboratory of Radio Frequency Heterogeneous Integration College of Electronics and Information EngineeringShenzhen UniversityShenzhen 518060China

Metasurfaces have demonstrated rich electromagnetic control capabilities and degrees of freedom in past years. As is well known, for passive metasurfaces, their functionalities cannot be further expanded accordingly once prototypes are established. Therefore, reconfigurable metasurfaces, utilizing active devices to replace geometric changes in passive structures, have received widespread attention, especially with the development of wireless communication recently. In reconfigurable metasurfaces, artificial meta-atoms are composed of active devices and passive structures combined together. However, these two modules are usually utilized as a whole due to the tight coupling of the active devices and the passive structures, which results in passive structures not receiving sufficient attention and being utilized as independent degrees of freedom. In this article, we propose the concept of weakly coupled reconfigurable metasurfaces in transmissive systems, enabling independent control of active and passive modules through weak coupling. As the proof of concept, a simple weakly coupled system is proposed, which can realize the transmission wavefront engineering through the geometric changes of meta-structures in passive mode, while achieving switching between transmission and reflection states in active mode, respectively. Our exploration lies in making use of the physical structure, which is easily neglected in traditional reconfigurable metasurface design, emphasizing the collaborative work of active and passive modules, exploring more available variables within the same aperture, and providing a potential solution for balancing functionality and resource consumption in practical applications.

关键词： modules coupling weakly

来源：评论

学校读者我要写书评

暂无评论

Partial multi-label learning with probabilistic graphical disambiguation 23

Partial multi-label learning with probabilistic graphical di...

引用

Proceedings of the 37th International Conference on Neural information Processing Systems

作者： Jun-Yi Hang Min-Ling Zhang School of Computer Science and Engineering Southeast University Nanjing China and Key Laboratory of Computer Network and Information Integration (Southeast University) Ministry of Education China

In partial multi-label learning (PML), each training example is associated with a set of candidate labels, among which only some labels are valid. As a common strategy to tackle PML problem, disambiguation aims to recover the ground-truth labeling information from such inaccurate annotations. However, existing approaches mainly rely on heuristics or ad-hoc rules to disambiguate candidate labels, which may not be universal enough in complicated real-world scenarios. To provide a principled way for disambiguation, we make a first attempt to explore the probabilistic graphical model for PML problem, where a directed graph is tailored to infer latent ground-truth labeling information from the generative process of partial multi-label data. Under the framework of stochastic gradient variational Bayes, a unified variational lower bound is derived for this graphical model, which is further relaxed probabilistically so that the desired prediction model can be induced with simultaneously identified ground-truth labeling information. Comprehensive experiments on multiple synthetic and real-world data sets show that our approach outperforms the state-of-the-art counterparts.

关键词：

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：