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

25,252 篇 会议
277 篇 期刊文献
21 册 图书
3 篇 学位论文

馆藏范围

25,553 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

15,800 篇 工学
- 9,866 篇 计算机科学与技术...
- 6,079 篇 电气工程
- 5,771 篇 信息与通信工程
- 5,615 篇 软件工程
- 2,016 篇 光学工程
- 1,453 篇 控制科学与工程
- 1,280 篇 机械工程
- 1,155 篇 电子科学与技术（可...
- 873 篇 生物医学工程（可授...
- 833 篇 生物工程
- 793 篇 仪器科学与技术
- 265 篇 网络空间安全
- 253 篇 化学工程与技术
- 245 篇 安全科学与工程
- 239 篇 交通运输工程
- 183 篇 材料科学与工程（可...
- 162 篇 土木工程
- 159 篇 建筑学
5,716 篇 理学
- 3,480 篇 物理学
- 2,207 篇 数学
- 886 篇 生物学
- 564 篇 统计学（可授理学、...
- 420 篇 系统科学
- 310 篇 化学
3,023 篇 医学
- 2,897 篇 临床医学
- 312 篇 基础医学(可授医学...
- 229 篇 药学(可授医学、理...
1,390 篇 管理学
- 850 篇 管理科学与工程(可...
- 612 篇 图书情报与档案管...
- 169 篇 工商管理
181 篇 法学
133 篇 农学
55 篇 教育学
52 篇 文学
51 篇 经济学
51 篇 军事学
22 篇 艺术学

主题

3,122 篇 image processing
2,084 篇 image coding
2,020 篇 visualization
1,752 篇 image segmentati...
1,486 篇 feature extracti...
1,081 篇 image reconstruc...
907 篇 cameras
885 篇 signal processin...
833 篇 image color anal...
756 篇 humans
712 篇 image edge detec...
688 篇 image enhancemen...
667 篇 computer vision
649 篇 training
582 篇 image analysis
567 篇 deep learning
536 篇 image quality
481 篇 conferences
472 篇 object detection
472 篇 robustness

机构

51 篇 school of electr...
50 篇 shanghai jiao to...
39 篇 ieee
38 篇 university of sc...
36 篇 shanghai jiao to...
36 篇 school of comput...
34 篇 shanghai jiao to...
33 篇 university of ch...
32 篇 microsoft resear...
26 篇 national institu...
25 篇 department of el...
24 篇 hendisli&#x011f
23 篇 institute for in...
23 篇 institute of ima...
23 篇 istanbul teknik ...
23 篇 institute of dig...
22 篇 peking univ inst...
21 篇 institute of inf...
21 篇 univ chinese aca...
21 篇 univ sci & techn...

作者

62 篇 guangtao zhai
46 篇 song li
45 篇 zhai guangtao
32 篇 jie yang
27 篇 li li
25 篇 m. vetterli
25 篇 bovik alan c.
25 篇 li sumei
25 篇 li song
25 篇 sarp ertürk
24 篇 jing zhang
24 篇 b. macq
23 篇 zhang lei
23 篇 li zhuo
23 篇 d.r. bull
22 篇 jürgen seiler
21 篇 shi guangming
20 篇 liu yang
20 篇 zhang wenjun
18 篇 mohamed-chaker l...

语言

24,740 篇 英文
489 篇 土耳其文
209 篇 其他
132 篇 中文
2 篇 西班牙文
2 篇 葡萄牙文

检索条件"任意字段=IEEE Visual Communications and Image Processing Conference"

共 25553 条记录，以下是91-100 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：

Local Overlapping Attentional Selection with VIT for image Classification in Remote Sensing

Local Overlapping Attentional Selection with VIT for Image C...

引用

2025 International conference on Electronics, Information, and Communication, ICEIC 2025

作者： Zou, ChangMan Jeon, Wang-Su Rhee, Sang-Yong University of Kyungnam Department of IT Convergence Engineering Changwon51767 Korea Republic of College of Computer Science and Technology Beihua University Jilin132013 China University of Kyungnam Department of Computer Engineering Changwon51767 Korea Republic of

ISBN: (纸本)9798331510756

Remote sensing image classification presents unique challenges due to the complexity of the scenes and the variability in visual features caused by the overhead perspective. Traditional convolutional neural networks (CNNs) struggle with long-range dependencies and extracting sufficient context for accurate classification. To address this, we propose the LSViT model, a novel approach that incorporates a local attention selection module into the Transformer architecture, specifically designed for remote sensing scene classification. LSViT enhances the classification performance by selecting discriminative tokens and removing redundant information. Our model leverages the Transformer's capacity for capturing both global and local features, improving the focus on important image regions. We evaluate LSViT on two benchmark datasets, AID and NWPU-RESISC45, and demonstrate its competitive performance, achieving state-of-the-art accuracy compared to traditional CNN and other Transformer-based methods. Notably, the local attention selection module enhances the model's ability to classify scenes with overlapping objects and complex backgrounds, making it an effective solution for large-scale remote sensing image classification tasks. © 2025 ieee.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Algorithm Implementation of Digital Protection System for Traditional Cultural Industry Based on Grey Clustering

Algorithm Implementation of Digital Protection System for Tr...

引用

2024 International conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Chen, Hongxia Hou, Lanbao School of Literature and Media Jingchu University of Technology Jingmen448000 China School of Mathematics and Physics Jingchu University of Technology Jingmen448000 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

The protection mode of digitalization effectively transforms various national traditional cultures into digital products, providing a way of thinking for the protection of national traditional cultures. This mode still lacks the mode of how to mine the data of national traditional culture and analyze the internal relationship structure after facing the massive data, which can guide the digital protection of national traditional culture under the complex social conditions in the future. This paper discusses the significance of digitalization for the protection of traditional national culture under the environment and ideology of big data development. The possibility of protecting traditional national culture based on big data was analyzed and discussed. This paper designs and establishes the digital perception analysis system of traditional culture. The system uses grey clustering algorithm to identify the characteristics of cultural products. The experimental results show that this method can improve the efficiency of traditional cultural product classification. This method has certain reference value for the research of digital protection system of traditional cultural industry. © 2025 SPIE.

关键词： Augmented reality visualization Telecommunications Computing systems Cultural heritage Data communications image processing Video Data storage Cameras

来源：评论

学校读者我要写书评

暂无评论

Role, Significance, and Impact of Method Noise in Multi-Modal Medical image Fusion 5

Role, Significance, and Impact of Method Noise in Multi-Moda...

引用

5th International conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Bhosekar, Shailesh Singh, Prabhishek Garg, Deepak Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Bennett University School of Computer Science Engineering and Technology Greater Noida India

ISBN: (纸本)9798331522100

Multi modal medical image fusion in, for instance, combining information from computed tomography (CT) scans, positron emission tomography (PET) and magnetic resonance imaging (MRI) into one single dataset, improves the accuracy of diagnostics due to atomistic and functional details of the images. In this paper, the role, importance, and effect of method noise in multi-modal medical image fusion, is considered to assess and improve fusion algorithms. The effectiveness of an algorithm can be determined in terms of its efficacy at preserving salient image content and removing unwanted artifacts while maintaining the former, which is defined by method noise, the residual noise after image processing. In this paper, I review the theoretical basis of method noise, discuss its function in both fusion and denoising processes, and discuss its practical and conceptual implications, showing its importance for quality assessment and algorithm refinement. We apply method noise to the Non-Subsampled Shearlet Transform (NSST) to demonstrate application in multi-modal medical image fusion. Comparative experiments using NSST based fusion with /without method noise demonstrate significantly different visual clarity and quantitative metrics as measured with different metrics. Results show that method noise both maintains image integrity by preventing detail loss and aids in the integration of complementary detail from different modalities. The need for method noise in advancing image fusion techniques is emphasized in this paper, and a framework for future research and application of fusion in diagnostic imaging is presented. © 2025 ieee.

关键词： Positron emission tomography

来源：评论

学校读者我要写书评

暂无评论

image Captioning Using Scene Graph Generation

Image Captioning Using Scene Graph Generation

引用

International conference on Wireless communications, Signal processing and Networking (WiSPNET)

作者： Shiny S Abisheak A Balaji P Rohit K Department of Artificial Intelligence Mepco Schlenk Engineering College Sivakasi India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

Understanding and generating natural language descriptions from images is a fundamental challenge in vision-language tasks within artificial intelligence. This paper introduces a novel image captioning framework that integrates scene graph generation to improve the semantic richness of generated captions. The proposed method employs the Relation Transformer (RelTR) model to extract structural representations from visual scenes in the form of subject-predicate-object triplets. A transformer-based captioning model then utilizes these structured scene graphs to produce fluent and contextually accurate captions. Experimental evaluations on the visual Genome dataset demonstrate that our approach yields superior semantic coherence and captioning accuracy compared to traditional image-to-text models. The incorporation of relational scene understanding results in captions that are more contextually informed and descriptive.

关键词： Wireless communication visualization Accuracy Semantics Genomics Signal processing Transformers SPICE Bioinformatics Context modeling

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of VGG16, MobileNet, and Ensemble Methods on Fundus image-Based Cataract Detection

A Comparative Study of VGG16, MobileNet, and Ensemble Method...

引用

2025 International conference on Advancement in Data Science, E-learning and Information System, ICADEIS 2025

作者： Syahda, Tabina Shafa Nabila Ma'ady, Mochamad Nizar Palefi Lidiawaty, Berlian Rahmy Telkom University Surabaya Department of Information Systems Surabaya Indonesia

ISBN: (纸本)9798331513320

Artificial Intelligence (AI) in ophthalmology has been growing, driven by the increasing volume of clinical data that can be utilized for algorithm development. image processing on fundus disease is crucial in providing visual information for cataract detection. Therefore, the application of technology that can leverage fundus images for cataract detection is still a few. In this regard, several previous studies have explored CNN algorithms for automatic cataract screening using fundus images. However, other research groups have proposed or developed new algorithms as alternatives. This research compares two CNN models, VGG16 and MobileNet, while also incorporating additional approaches such as Ensemble Learning and Hybrid Method. VGG16 and MobileNet were chosen because they are known for their high accuracy performance and computational efficiency. Source data obtained from Kaggle as many as 1000 datasets. The results of the study indicate that the model with the Ensemble Learning approach achieved the highest average accuracy, followed by MobileNet, MobileNet + SVM, VGG16, and VGG16 + SVM, with accuracies of 0.9377;0.9150;0.9143;0.9129;and 0.9104, respectively. This research is expected to aid medical professionals in diagnosing cataracts more accurately and guide engineers in selecting the best machine-learning models for fundus image-based cataract detection systems. © 2025 ieee.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Bibliometric Analysis of Road Distress Detection Based on Citespace 24

Bibliometric Analysis of Road Distress Detection Based on Ci...

引用

5th International conference on Computer Science and Management Technology, ICCSMT 2024

作者： Li, Yaoye Zhang, Yinbo He, Rong Ma, Lianxia Chen, Fang Xinjiang communications Construction Group Co. Ltd. Xinjiang Urumqi China Xinjiang Key Laboratory of Transportation Prefabricated Construction and Maintenance Xinjiang Urumqi China Xinjiang University Xinjiang Urumqi China

ISBN: (纸本)9798400709999

To analyze the research progress in the field of road disease detection, this article searched the Web of Science Core Collection database for papers related to road disease detection from 2000 to *** CiteSpace software, a visual analysis was conducted on the 247 retrieved documents, focusing on annual publication numbers, publishing countries, core institutions and authors, keywords, burst words, and timeline mapping to explore the current status and trends in this *** findings indicate that since 2004, the overall research trend in road disease detection has been on an upward trajectory, with a notable increase in the number of research papers published in 2021, reflecting a significant surge in research ***, China, the United States, and Italy have been the most prolific in research *** leading research institutions are primarily scientific and technological academies, with Chang'an University taking a dominant position in the field of road disease *** keyword co-occurrence analysis, burst detection, and keyword clustering analysis, it was determined that disease detection technology, deep learning and machine learning, image processing and intelligent analysis, and system integration and development have been the research hotspots in the road disease detection field from 2000 to *** is anticipated that future research will evolve towards the directions of performance evaluation, multimodal data fusion, and real-time monitoring and analysis. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Data fusion

来源：评论

学校读者我要写书评

暂无评论

Spk2ImgMamba: Spiking Camera image Reconstruction with Multi-Scale State Space Models

Spk2ImgMamba: Spiking Camera Image Reconstruction with Multi...

引用

2025 ieee/CVF Winter conference on Applications of Computer Vision, WACV 2025

作者： Yin, Jiaoyang Fan, Bin Xu, Chao Huang, Tiejun Shi, Boxin School of Computer Science Peking University State Key Lab of Multimedia Info. Processing China School of Computer Science Peking University Nat'l Eng. Research Ctr. of Visual Technology China School of Intelligence Science and Technology Peking University Nat'l Key Lab of General Ai China

ISBN: (纸本)9798331510831

As a bio-inspired vision sensor, the spiking camera has showcased remarkable capability in high-speed imaging with a sampling rate of 40,000 Hz. Reconstructing clear images from continuous spike streams, which is obtained by each photosensor continuously detecting photons and firing them asynchronously, has garnered significant attention. Despite promising results, existing spike-to-image reconstruction methods face challenges in balancing global receptive fields and efficient computation due to the inherent limitations of their backbones. Recently, due to powerful long-range modeling and linear complexity, the state space model (SSM) has emerged as a competitive alternative to CNNs and Transformers. In this paper, we propose a lightweight spike-to-image reconstruction network that harnesses Mamba as the backbone. Our approach sequentially executes three core modules: temporal information integration, spatial feature enhancement, and progressive image reconstruction. The former accumulates cues across diverse temporal windows to explore both long-term and short-term contexts. Subsequently, to model global dependencies while heightening local detail perception, we develop a multi-scale SSM block characterized by multi-scale multi-direction scanning, which effectively boosts spatial feature representations. Finally, intensity images are decoded progressively from the enhanced light-intensity features. Extensive experiments on both synthetic and real-captured data demonstrate that our approach achieves state-of-the-art performance, with only 10% of the network parameters and nearly two orders of magnitude less computational effort. The code will be available at https://***/interstellarH/Spk2ImgMamba. © 2025 ieee.

关键词： Bioimaging

来源：评论

学校读者我要写书评

暂无评论

3rd International conference on Computing and Communication Networks, ICCCN 2023

3rd International Conference on Computing and Communication ...

引用

3rd International conference on Computing and Communication Networks, ICCCN 2023

ISBN: (纸本)9789819726707

The proceedings contain 60 papers. The special focus in this conference is on Computing and Communication Networks. The topics include: Enhancing Security in Wireless Sensor Networks: A Broadcast/Multicast Authentication Framework with Identity-Based Signature Schemes;TSFTO: A Two-Stage Fuzzy-Based Tasks Orchestration Algorithm for Edge and Fog Computing Environments;tracking Climatic Variations Through Smart IoT-Driven Approach: An Exploratory Analysis;Design and Manufacturing of an Efficient Low-Cost Fire Surveillance System Based on GSM communications and IoT Technology;a Comparative Analysis of Optimized Routing Protocols for High-Performance Mobile Ad Hoc Networks;integrating Sandpiper Optimization Algorithm and Secure Aware Routing Protocol for Efficient Cluster Head Selection in Wireless Sensor Networks;the Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks;Using Wireless Sensor Network Performance and Optimizing in Underground Mines with Virtual MIMO Antenna;a Novel Logistic Regression-Based Fire Detection Model Using IoT in Underground Coal Mines;An MQTT IoT Intrusion Detection System Using Deep-Learning;multi-objective Optimal Feature Selection for Cyber Security Integrated with Deep Learning;application of Gradient Boosting Classifier-Based Computational Intelligence to Detect Drug Addiction Threat in Society;insurance 4.0: Smart Insurance Technologies and Challenges Ahead;review on Vision Transformer for Satellite image Classification;primitive Roots and Euler Totient Function-Based Progressive visual Cryptography;approach for Fire Detection Using image processing;review of Various Approaches for Authorship Identification in Digital Forensics;machine Learning Model for Traffic Prediction and Pattern Extraction in High-Speed Optical Networks;improved Markov Decision Process in Wireless Sensor Network for Optimal Energy Consumption.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Language-Guided Semantic Alignment for Point Cloud-Based 3D Scene Graph Generation

Language-Guided Semantic Alignment for Point Cloud-Based 3D ...

引用

2025 International conference on Electronics, Information, and Communication, ICEIC 2025

作者： Lee, Suhyeon Jeong, Jinwoo Jeong, Taehyun Kim, Sungjei Intelligent Image Processing Research Center Korea Electronics Technology Institute Seongnam Korea Republic of School of Computer Science and Engineering Korea University of Technology and Education Cheonan Korea Republic of

ISBN: (纸本)9798331510756

In this paper, we propose a novel model called LAP, Language-guided semantic Alignment for Point cloud-based 3D semantic scene graph generation. Point cloud-based 3D scene graph generation is the task of predicting the category of each instance present in a 3D point cloud scene and the relationships between them. Our model leverages text embeddings for objects, predicates, and triplets during network training, enabling the network to generate reliable semantic scene graphs. To this end, we introduce three loss functions that leverage text embed dings to semantically align the features for scene graph prediction. Comparative experiments with previous methods on the 3DSSG dataset demonstrate the effectiveness of the LAP model. © 2025 ieee.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

VPCI: Self-Supervised visual Prompt-Guided Cross-Domain Interactive image Fusion Framework

VPCI: Self-Supervised Visual Prompt-Guided Cross-Domain Inte...

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yong Liu Chengyu Wu Jiayuan Cui Bin Jiang Shenzhen Research Institute of Shandong University Shenzhen China School of Mechanical Electrical & Information Engineering Shandong University Weihai China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

image fusion combines information from multi-modality images to produce high-quality fused images with enhanced clarity, contrast, and informativeness. However, limited ground truth fusion data lead to difficulties in effectively training these fusion models. Moreover, current studies lack of fine-grained, domain style-specific guidance during image fusion processing. To address these issues, we propose a self-supervised visual Prompt-guided Cross-Domain Interactive image fusion framework (VPCI), which introduces a visual Prompt Generation (VPG) strategy that embeds visual features from different modalities as prompts, guiding the model to learn complementary information. Furthermore, to better integrate modality-specific styles, we introduce a Cross-domain Prompt-guided Interaction (CPI) module to generate information-rich fusion images by fully interacting with visual prompts. Experimental results show that our framework outperforms existing state-of-the-art methods. The code is available at https://***/liwead/VPCI.

关键词： Training visualization Codes Signal processing Data models Acoustics High frequency Speech processing image fusion

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 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：