检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

20,250 篇 会议
161 篇 期刊文献
80 册 图书
1 篇 学位论文

馆藏范围

20,492 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,756 篇 工学
- 8,297 篇 计算机科学与技术...
- 5,001 篇 软件工程
- 4,986 篇 信息与通信工程
- 4,636 篇 电气工程
- 1,447 篇 控制科学与工程
- 1,319 篇 电子科学与技术（可...
- 1,225 篇 光学工程
- 898 篇 生物医学工程（可授...
- 868 篇 机械工程
- 830 篇 仪器科学与技术
- 811 篇 生物工程
- 326 篇 网络空间安全
- 291 篇 交通运输工程
- 284 篇 安全科学与工程
- 280 篇 化学工程与技术
- 247 篇 动力工程及工程热...
- 189 篇 建筑学
- 179 篇 土木工程
4,663 篇 理学
- 2,150 篇 数学
- 2,073 篇 物理学
- 874 篇 生物学
- 668 篇 统计学（可授理学、...
- 521 篇 系统科学
- 330 篇 化学
1,523 篇 医学
- 1,405 篇 临床医学
- 383 篇 基础医学(可授医学...
- 269 篇 药学(可授医学、理...
1,368 篇 管理学
- 824 篇 管理科学与工程(可...
- 615 篇 图书情报与档案管...
- 208 篇 工商管理
204 篇 法学
136 篇 农学
78 篇 经济学
69 篇 军事学
64 篇 教育学
40 篇 文学
24 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

1,121 篇 image segmentati...
1,066 篇 image coding
1,059 篇 signal processin...
1,009 篇 image processing
987 篇 internet of thin...
953 篇 feature extracti...
829 篇 image reconstruc...
632 篇 internet
553 篇 signal processin...
497 篇 signal to noise ...
476 篇 deep learning
476 篇 image edge detec...
458 篇 training
424 篇 image color anal...
400 篇 cameras
397 篇 robustness
396 篇 image enhancemen...
306 篇 image resolution
292 篇 image recognitio...
288 篇 accuracy

机构

58 篇 school of inform...
39 篇 university of sc...
37 篇 signal processin...
29 篇 microsoft resear...
27 篇 university of ch...
26 篇 institute of sig...
26 篇 signal processin...
25 篇 center for signa...
24 篇 university of el...
23 篇 school of electr...
21 篇 ieee
20 篇 school of cyber ...
20 篇 department of si...
20 篇 school of inform...
20 篇 signal and infor...
20 篇 school of electr...
20 篇 college of big d...
19 篇 hsch darmstadt d...
19 篇 peng cheng labor...
19 篇 harbin institute...

作者

31 篇 li zhuo
27 篇 zhuo li
25 篇 sridharan sridha
23 篇 yang yang
23 篇 r.m. mersereau
20 篇 jing zhang
20 篇 wei li
20 篇 gabbouj moncef
19 篇 mansouri majdi
18 篇 zhang lei
18 篇 busch christoph
18 篇 m. gabbouj
17 篇 m.j.t. smith
17 篇 bouzrara kais
17 篇 clinton fookes
17 篇 wang wei
17 篇 zhang yan
16 篇 wang lei
16 篇 takahiro ogawa
16 篇 ghassan alregib

语言

19,133 篇 英文
1,273 篇 其他
78 篇 中文
7 篇 俄文
6 篇 土耳其文
1 篇 西班牙文

检索条件"任意字段=IEEE International Conference on Signal Image Technology and Internet Based Systems"

共 20492 条记录，以下是981-990 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

INTERPRETABILITY AND COMPLEXITY REDUCTION IN IOT NETWORK ANOMALY DETECTION VIA XAI 49

INTERPRETABILITY AND COMPLEXITY REDUCTION IN IOT NETWORK ANO...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Nascita, Alfredo Carillo, Raffaele Giampetraglia, Federica Iacono, Antonio Persico, Valerio Pescape, Antonio Univ Napoli Federico II Naples Italy

ISBN: (纸本)9798350374520;9798350374513

Due to their versatility and effectiveness, Deep Learning (DL) approaches are increasingly used in designing Network Intrusion Detection systems (NIDSs). Specifically, Anomaly Detection (AD) approaches such as AutoEncoders proved suitable when malicious traffic for training is not available. However, understanding how and why DL models provide a certain decision is often challenging, since they are often considered black boxes. In this paper, we develop a methodology based on SHAP-a well-known eXplainable Artificial Intelligence (XAI) technique-to elucidate the contribution of traffic features to the decisions of anomaly detectors. The interpretability gained through our methodology facilitates a deeper understanding of the characteristics of network traffic that drive the detection process. We evaluate our methodology on two recent IoT datasets including attack traffic (Kitsune and IoT-23). Leveraging the interpretability results, our investigation yields substantial enhancements in model complexity (up to -98%) without compromising its detection capabilities. The experimental results underscore the potential of XAI in refining and advancing the landscape of NIDSs.

关键词： internet of Things eXplainable Artificial Intelligence Intrusion Detection System Anomaly Detection

来源：评论

学校读者我要写书评

暂无评论

LOCAL AND GLOBAL FEATURE ADAPTIVE ADJUSTMENT NETWORK FOR REMOTE SENSING image SCENE CLASSIFICATION 49

LOCAL AND GLOBAL FEATURE ADAPTIVE ADJUSTMENT NETWORK FOR REM...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Cao, Feng Liu, Chang Li, Deyu Qian, Yuhua Zhang, Chao Zhang, Hu Shanxi Univ Sch Comp & Informat Technol Sch Big Data Taiyuan 030006 Peoples R China Shanxi Univ Key Lab Computat Intelligence & Chinese Informat Minist Educ Taiyuan 030006 Peoples R China Shanxi Univ Inst Big Data & Ind Taiyuan 030006 Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Convolutional neural network (CNN)-based methods have been extensively used for remote sensing scene classification (RSSC) and have obtained remarkable classification results. However, its limitations in extracting global features have hindered further improvement. Transformers can directly capture global features through self-attention mechanisms, but they have deficiencies in modeling local features. Currently, an approach that directly combines CNN and Transformer features may lead to feature imbalance, and introduce redundant information. To address these problems, we propose a local and global feature adaptive adjustment network (LGFAANet) for RSSC. First, we employ a dual-branch network structure to extract local and global features from remote sensing scene images. Second, we design a local and global feature adaptive adjustment module (LGFAA) to dynamically allocate weights to the features. Third, we use a multi-layer feature aggregation module (MLFA) to aggregate the adjusted features, thereby further enhancing feature representation. Finally, we introduce joint loss to accelerate network convergence, while reducing intra-class distance and increasing inter-class distance. Experimental results demonstrate that our proposed method displays enhanced feature representation ability and outperforms existing state-of-the-art methods.

关键词： CNN Transformer feature adaptive adjust RSSC

来源：评论

学校读者我要写书评

暂无评论

Real-Time Semantic Segmentation for Autonomous Scale Cars using Mixed Real and Synthetic Data 10

Real-Time Semantic Segmentation for Autonomous Scale Cars us...

引用

10th international conference on Mechatronics and Robotics Engineering (ICMRE)

作者： Ehrenfeuchter, Steffen Corlito, Roberto Marchthaler, Reiner Enzweiler, Markus Esslingen Univ Appl Sci Inst Intelligent Syst Esslingen Germany

ISBN: (纸本)9798350394283;9798350394276

This paper presents a real-time semantic segmentation framework for camera-based environment perception of objects and infrastructure elements in autonomous scale cars. It is specifically targeted towards student competitions such as the Carolo Cup or the Bosch Future Mobility Challenge. To reduce pixel-wise manual annotation efforts, our framework involves a mixture of both synthetic and real image data, carefully tuned towards the unique requirements of the given scenario. Real images are acquired from a 1:10 scale vehicle equipped with a single monocular camera and are manually annotated. Synthetic image data with automatic pixel-wise annotation is obtained via a custom Unity-based simulation pipeline. We evaluate various mixed real-synthetic data strategies to train different state-of-the-art deep neural networks with a focus on both segmentation performance and real-time capability using an NVIDIA Jetson AGX Xavier platform as in-vehicle test bed. Our experimental results show a significant improvement in semantic segmentation performance of the mixed real-synthetic data approach at real-time speeds of approximately 60 FPS on the target platform.

关键词： Mobile Robotics Autonomous systems Robot Intelligence and Learning signal and image Processing

来源：评论

学校读者我要写书评

暂无评论

Automatic closed-loop test technology of smart gateway based on mobile internet technology 4

Automatic closed-loop test technology of smart gateway based...

引用

4th ieee international conference on Power, Intelligent Computing and systems, ICPICS 2022

作者： Quan, Xu Qiyuan, Xu Xinhao, Lin Nan, Ma Lei, Yu Yinliang, Liu Electric Power Research Institute CSG Guangzhou510663 China Shenzhen Power Supply Bureau Shenzhen518022 China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

The application of mobile internet technology in the test of power distribution terminal is analyzed, and the mobile system architecture of the test terminal is explained. The closed loop test system of the intelligent network is analyzed, and the system architecture, test process, hardware principle, and test function are proposed. Specific analysis is carried out on the test method of smart gateway based on mobile internet, including the test method and process of single smart gateway, the test method and process of multiple smart gateways, and the modular test method of smart gateway. The three-remote test of the power distribution terminal is used as a case for simulation calculation. Through the voltage signal, current signal and switch position of the test results, the effectiveness of the proposed mobile interconnection test method is demonstrated. © 2022 ieee.

关键词： Gateways (computer networks)

来源：评论

学校读者我要写书评

暂无评论

A Dual Branch Segmentation Network for Forward-looking Sonar image

A Dual Branch Segmentation Network for Forward-looking Sonar...

引用

2023 ieee international conference on signal Processing, Communications and Computing, ICSPCC 2023

作者： He, Ju Chen, Jianfeng Xu, Hu School of Marine Science and Technology Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9798350316728

Accurate segmentation of marine objects holds crucial significance and value in underwater resource exploration and marine rescue. However, in complex and noisy underwater environments, existing CNN-based algorithms face limitations such as insufficient global feature extraction capabilities and incomplete segmentation of certain targets in the sonar image. To overcome these inevitable problems, this article innovatively introduces a segmentation network based on transformer blocks. The algorithm encompasses a dual-branch structure that involves local and global feature extraction. The main components of the algorithm include four parts: image preprocessing, Local feature extraction branch, Global feature extraction branch and Segmentation head. Finally, we conducted experiments on the public dataset, and the mIoU value of the proposed method surpasses other CNN-based algorithms. The results illustrate the effectiveness and feasibility of the segmentation network. © 2023 ieee.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Traffic Assistance and Control System- An RFID Approach

Traffic Assistance and Control System- An RFID Approach

引用

2023 international conference on Computer Communication and Informatics, ICCCI 2023

作者： Kalaiarasi, A. Raja, L. Velmurugan, S. Shanthi, G. Ariharan, R. Kumareshan, N. Sri Shakthi Institute of Engineering and Technology Department of EEE Coimbatore India Sri Eshwar College of Engineering Department of ECE Coimbatore India Dr.N.G.P Institute of Technology Department of Biomedical Engineering Coimbatore India Sri Krishna College of Technology Department of ECE Coimbatore India Guide House Chennai India

ISBN: (纸本)9798350348217

All intelligent objects are connected through a worldwide network called the internet of Things (IoT).. It serves as the conduit via which all things can communicate with one another. The term internet of vehicles is used when those intelligent items are limited to solely connected vehicles. It uses an electronic-based traffic violation monitoring setup rather than assigning a specific officer to keep an eye on traffic violations. This is a mechanism for electronically filing complaints and collecting fee It uses RFID technology to allow for the direct debiting of fees and complaint booking from the associated prepaid account. This clever technique assists the government and the populace in preventing traffic signal violations and punishing the defaulters. Because of this system, citizens are more likely to be motivated to obey traffic light laws, and the government finds it simpler to automatically monitor and manage the system. The internet of Vehicles (IoV), which is built on an intelligent traffic management system, has high interoperability, is simple to upgrade, and can replace current traffic control systems. The proposed system's low cost can greatly enhance traffic signal monitoring and control. The internet of Vehicles uses a network of wireless sensors, detection technologies, and the internet to autonomously track, manage, monitor, and process traffic objects. The proposed system's fundamental features take care to simplify living. © 2023 ieee.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

Covid-19 Classification using Fine-tuned EfficientNet Architecture 9

Covid-19 Classification using Fine-tuned EfficientNet Archit...

引用

9th ieee international conference for Convergence in technology, I2CT 2024

作者： Sruthi, Srigiri Emadaboina, Siddharth MacHavarapu, Pradyumna Singh, Rimjhim Padam Kanchan, Sneha Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Engineering Bengaluru India Universiti Tunku Abdul Rahman Department of Internet Engineering And Computer Science Malaysia

ISBN: (纸本)9798350394474

This work utilizes an Efficient Net-based deep learning architecture, leveraging its efficiency and scalability for image classification tasks. We employ a Dataset of chest X-ray images, including COVID-19 cases as well as other relevant Pathology, to train and evaluate the model. The training process involves data augmentation, model optimization, and early stopping to ensure robust and generalizable performance. It specifies the image size, channels, and class count, and then proceeds to create a pre-trained model using the EfficientNetB0 architecture. The model is built upon the pre-trained EfficientNetB0 model, with additional layers including Layer Normalization, Dense, and Dropout layers for fine-tuning on the Covid-19 data. Subsequently, the model is rigorously evaluated using standard performance metrics, including precision, recall, F1-score, and accuracy, and has proven to outperform other state-of-art models by a 3% increase in F1-score value. © 2024 ieee.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

SELF-TRAINING DOMAIN ADAPTATION VIA WEIGHT TRANSMISSION BETWEEN GENERATORS 49

SELF-TRAINING DOMAIN ADAPTATION VIA WEIGHT TRANSMISSION BETW...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Wei, Xing Ji, Zhaoxin Yang, Fan Zhao, Chong Wen, Bin Lu, Yang Hefei Univ Technol Sch Comp & Informat Hefei Peoples R China Hefei Univ Technol Intelligent Mfg Technol Res Inst Hefei Peoples R China Anhui Mine IOT & Secur Monitoring Technol Key Lab Minist Educ Anhui Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Unsupervised domain adaptation (UDA) aims to transfer knowledge from the labeled source domain to the fully-unlabeled target domain, thus improving the classification performance of the target domain. Recently, self-training has shown its effectiveness on UDA. However, the feature space for generating pseudo-labels contains a large amount of source information, making it challenging for the generator to learn discriminative features of the target domain. In this paper, we propose a self-training domain adaptation model via weight transmission between generators (WTBG). Specifically, we develop a bi-directional transmission structure for generators, using Exponential Moving Average (EMA) as the bridge between two generators. By cyclically transmitting weight parameters between them, alleviate the difficulty of generators in learning target features. And a pseudo-label filter based on cosine similarity is designed to reduce the influence of error pseudo-labels. Extensive experiments conducted on two benchmark UDA datasets show that WTBG has superior classification performance.

关键词： Domain adaptation Self-training image classification

来源：评论

学校读者我要写书评

暂无评论

image-assisted Label Connective Completion for Vessel Segmentation with Insufficient Annotations

Image-assisted Label Connective Completion for Vessel Segmen...

引用

2025 ieee international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Zheng, Xiaoqi Yang, Baoyao Fang, Xiuwen Yao, Wenfang Ye, Mang School of Computer Science and Technology Guangdong University of Technology China School of Computer Science Wuhan University China School of Nursing The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9798350368741

Automatic and accurate vessel segmentation is crucial for disease diagnosis. Deep learning methods are widely used, but their promising results rely on accurately annotated data. Due to complex vessel morphology and low-contrast image, accurate vessel delineation poses a practical challenge, resulting in insufficient annotations, which is a prominent form of noisy labels. This paper proposes an image-assisted Label Connective Completion method, which enhances label's vessel information by images under the supervision of connectivity to address insufficient annotation issue. Specifically, we develop an image-guided Vessel Enhancement module, which transmits structural information extracted from images based on label navigation to label space, promoting completion of missing annotated parts in original labels. In addition, a branch completion-connectivity loss is designed and introduced as an auxiliary supervision to prevent vessel branch disconnection during label completion. Experimental results on DRIVE, CHASE_DB1 and DCA1 datasets demonstrate that our method outperforms existing noisy labels learning methods. © 2025 ieee.

关键词： Insufficient annotation Label completion Vessel segmentation

来源：评论

学校读者我要写书评

暂无评论

A METHOD FOR X-RAY image LANDMARKS LOCALIZATION USING CYCLIC COORDINATE-GUIDED STRATEGY 49

A METHOD FOR X-RAY IMAGE LANDMARKS LOCALIZATION USING CYCLIC...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Wang, Xianglong An, Xifeng Rigalll, Eric Zhang, Shu Yu, Hui Dong, Junyu Ocean Univ China Qingdao Peoples R China Univ Portsmouth Portsmouth Hants England

ISBN: (纸本)9798350344868;9798350344851

In this study, we present a novel method for pinpointing landmarks in X-ray images, which simultaneously offers computational efficiency and localization precision. Our method leverages a cyclic coordinate-guided strategy that requires fewer model parameters and lower computational costs than traditional heatmap-based supervised methods. This is crucial for medical imaging applications where imaging devices often have limited computational resources yet require high-precision landmark localization. Our methodology involves a two-stage process that employs cyclic inference to optimize landmark localization. In the first stage, non-uniform sampling is used to capture the multi-scale features of landmarks. This is followed by a second stage in which cyclic training fine-tunes the landmark coordinates towards their optimal positions. Our results indicate that our two-stage process achieves competitive localization performance with state-of-the-art methods yet with added benefits of lower computational overhead and smaller parameter count. Additionally, a global block was developed to capture global position information of landmarks, and experiments showed its effectiveness and its contribution in enhancing the model's landmark localization accuracy. We validated our method using two publicly available datasets, and the source code for our experiments is available on GitHub: https://***/switch626/***.

关键词： X-ray images landmark localization deep learning cyclic coordinate-guided

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 95 96 97 98 99 100 101 102 103 104 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：