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

3,724 篇 会议
51 册 图书
47 篇 期刊文献
1 篇 学位论文

馆藏范围

3,823 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,051 篇 工学
- 1,453 篇 计算机科学与技术...
- 983 篇 软件工程
- 703 篇 信息与通信工程
- 388 篇 电气工程
- 208 篇 光学工程
- 207 篇 控制科学与工程
- 195 篇 生物工程
- 159 篇 电子科学与技术（可...
- 143 篇 机械工程
- 125 篇 生物医学工程（可授...
- 124 篇 仪器科学与技术
- 73 篇 化学工程与技术
- 64 篇 网络空间安全
- 60 篇 材料科学与工程（可...
- 54 篇 建筑学
- 53 篇 土木工程
- 42 篇 安全科学与工程
970 篇 理学
- 559 篇 物理学
- 285 篇 数学
- 209 篇 生物学
- 87 篇 统计学（可授理学、...
- 71 篇 化学
- 68 篇 系统科学
398 篇 管理学
- 241 篇 图书情报与档案管...
- 181 篇 管理科学与工程(可...
- 66 篇 工商管理
228 篇 医学
- 204 篇 临床医学
- 68 篇 基础医学(可授医学...
- 48 篇 药学(可授医学、理...
72 篇 法学
- 68 篇 社会学
43 篇 教育学
38 篇 农学
24 篇 文学
21 篇 经济学
14 篇 军事学
7 篇 艺术学
1 篇 历史学

主题

566 篇 visualization
318 篇 visual communica...
231 篇 image processing
204 篇 feature extracti...
156 篇 image coding
118 篇 training
97 篇 multimedia commu...
95 篇 accuracy
93 篇 semantics
91 篇 signal processin...
91 篇 humans
87 篇 deep learning
87 篇 cameras
85 篇 computational mo...
83 篇 image segmentati...
83 篇 computer vision
78 篇 streaming media
72 篇 data visualizati...
71 篇 image color anal...
70 篇 information proc...

机构

24 篇 school of commun...
22 篇 institute of ima...
20 篇 school of inform...
20 篇 communication un...
16 篇 communication un...
15 篇 school of electr...
14 篇 school of inform...
13 篇 school of inform...
12 篇 institute of ima...
9 篇 waseda universit...
8 篇 school of remote...
8 篇 information engi...
8 篇 graduate institu...
8 篇 lanzhou universi...
8 篇 institute of inf...
7 篇 institute of inf...
7 篇 school of inform...
7 篇 communication un...
7 篇 institute of ima...
6 篇 institute for in...

作者

25 篇 guangtao zhai
15 篇 sumei li
14 篇 xiongkuo min
11 篇 xiaokang yang
10 篇 zhenzhong chen
9 篇 zhai guangtao
9 篇 zhongpai gao
9 篇 shan liu
7 篇 yang yang
7 篇 lu yu
7 篇 hiroshi ishikawa
7 篇 wen gao
6 篇 ping an
6 篇 wenjun zhang
6 篇 hongliang li
6 篇 tomas pajdla
6 篇 cheng-lin liu
6 篇 dorothea kolossa
6 篇 khursheed khursh...
6 篇 liu wei

语言

3,753 篇 英文
43 篇 其他
26 篇 中文
4 篇 土耳其文
1 篇 俄文

检索条件"任意字段=Conference on Visual Information Processing and Communication IV"

共 3823 条记录，以下是21-30 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：

Generation of Scene Graph and Semantic Image: A Review and Challenge Ahead

Generation of Scene Graph and Semantic Image: A Review and C...

引用

International conference on Artificial Intelligence in information and communication (ICAIIC)

作者： Shao-Kai Hsieh Huey-Ing Liu Department of Electrical Engineering Fu Jen Catholic University New Taipei City Taiwan

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

Scene graph generation creates a structured representation of visual scenes by identifying objects and their attributes and the relationships between them. Conversely, semantic image generation converts semantic representations such as scene graphs, textual descriptions, or object layouts, into photorealistic images. This paper provides an overview of recent advancements in generations of scene graph and semantic image. The survey explores how innovations in both fields can complement each other, paving the way for advanced applications in autonomous systems, semantic communication, visual reasoning, and creative industries. Challenges such as data imbalance, scalability, and semantic coherence and future research directions including multimodal integration, prior processing etc. are throughly discussed.

关键词： Surveys visualization Technological innovation Image synthesis Reviews Scalability Semantics Semantic communication Artificial intelligence Photorealistic images

来源：评论

学校读者我要写书评

暂无评论

ALIC: Adaptive Fusion Entropy Model for Learned Image Compression

ALIC: Adaptive Fusion Entropy Model for Learned Image Compre...

引用

2025 IEEE International conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Li, Lingxue Liu, Meiqin Zhang, Yifan Tang, Qi Yao, Chao Zhao, Yao Institute of Information Science Beijing Jiaotong University Beijing China Visual Intelligence + X International Cooperation Joint Laboratory of MOE Beijing Jiaotong University China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798350368741

Recently, learned image compression algorithms have achieved significant performance. The entropy model is crucial for improving the rate-distortion performance by estimating the probability distribution of latent representation. In this paper, we propose an adaptive fusion entropy model for learned image compression (ALIC). To explore the correlation between channel and global spatial features, an adaptive fusion entropy model (AFEM) is designed. AFEM first slices the latent representation along the channels and leverages the adaptive channel fusion context module (ACFC) to capture correlations between the decoded and current slices. Subsequently, AFEM uses the adaptive spatial fusion context module (ASFC) to further divide the current slice into encoding pixels and reference pixels, thus improving the accuracy of probability estimation. The attention map and modulation parameter are introduced in ACFC and ASFC to interact with channel and spatial features. In addition, the variable-rate residual transformer (VResFormer) is proposed to control dynamic bit-rate by selectively modulating the high-frequency component according to coefficient weight and bias. Experimental results indicate that our ALIC outperforms other learned image compression algorithms. Our ALIC saves 5.89% bit-rate compared with VVC (4:4:4) on Kodak dataset. © 2025 IEEE.

关键词： Entropy model Learned image compression Variable-rate

来源：评论

学校读者我要写书评

暂无评论

MixSense : Mixture of Vision Sense

MixSense : Mixture of Vision Sense

引用

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

作者： Jian Lin Zhuoran Wang Qibo Qiu Jianzhong Chen Zixian Ge Weizhong Jin Yuchao Yan Li Yu Research & Innovation Institute China Mobile (Zhejiang) Hangzhou China School of Computing and Information University of Pittsburgh Pittsburgh The United States

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

It is a new trend to fine-tune Large Multimodal Models (LMMs) to adapt to specific visual tasks through task-related conversation data. This approach provides a new paradigm for solving various vision-language tasks, however, it still faces two problems: (1) the global visual features input to the backbone Large Language Model (LLM) lack the focus on task-specific information, which may lead a sub-optimal performance on specific visual tasks; (2) The hallucinations on specific tasks are underestimated, which makes the model prone to factual errors during inference. In order to solve these two problems, we propose MixSense, a new LMM paradigm that aligns the visual features of specilized models and general models to the backbone LLM together, increasing the focus on specific task information while maintaining the vanilla capabilities of the model; evaluated and fine-tuned with the constructed task-specific negative samples, we can further assess the degree of hallucinations of the model on specific visual tasks and reduce it. We validate our method on a popular Object Detection (OD) task, Referring Expression Comprehension (REC), and extensive experiments demonstrate the effectiveness of our proposal.

关键词： Training visualization Pipelines Oral communication Object detection Signal processing Lead Market research Proposals Speech processing

来源：评论

学校读者我要写书评

暂无评论

Towards Dynamic Neural communication and Speech Neuroprosthesis Based on Viseme Decoding

Towards Dynamic Neural Communication and Speech Neuroprosthe...

引用

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

作者： Ji-Ha Park Seo-Hyun Lee Soowon Kim Seong-Whan Lee Dept. of Artificial Intelligence Korea University Seoul Republic of Korea Dept. of Brain and Cognitive Engineering Korea University Seoul Republic of Korea

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Decoding text, speech, or images from human neural signals holds promising potential both as neuroprosthesis for patients and as innovative communication tools for general users. Although neural signals contain various information on speech intentions, movements, and phonetic details, generating informative outputs from them remains challenging, with mostly focusing on decoding short intentions or producing fragmented outputs. In this study, we developed a diffusion model-based framework to decode visual speech intentions from speech-related non-invasive brain signals, to facilitate face-to-face neural communication. We designed an experiment to consolidate various phonemes to train visemes of each phoneme, aiming to learn the representation of corresponding lip formations from neural signals. By decoding visemes from both isolated trials and continuous sentences, we successfully reconstructed coherent lip movements, effectively bridging the gap between brain signals and dynamic visual interfaces. The results highlight the potential of viseme decoding and talking face reconstruction from human neural signals, marking a significant step toward dynamic neural communication systems and speech neuroprosthesis for patients.

关键词： visualization communication systems Lips Neuroprostheses Signal processing Phonetics Brain modeling Decoding Speech processing Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

DeepFakeGuard: Safeguarding Digital Platforms Against Fake Profiles Using AI 4

DeepFakeGuard: Safeguarding Digital Platforms Against Fake P...

引用

4th International conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Swarna Sudha, M. Manjula, S. Bharathi, Indira Krishnasamy, Valarmathi Vijayalakshmi, K. Ramco Institute of Technology Department of Computer Science and Engineering Rajapalayam India School of Computer Science and Engineering Vellore Institute of Technology Chennai India PSR Engineering College Department of Electronics and Communication Engineering Sivakasi India

ISBN: (纸本)9798331523923

This research introduces DeepFakeGuard, a hybrid deep learning framework designed to detect fake profiles on social media platforms, addressing the growing threat of fraudulent accounts online. DeepFakeGuard integrates multiple data modalities, including textual, visual, behavioral, and network features, to accurately classify profiles as real or fake. Leveraging advanced deep learning models such as BERT for textual analysis, ResNet for image processing, and LSTM for modeling behavioral patterns, DeepFakeGuard provides a comprehensive and robust solution for identifying fake profiles across diverse platforms. The framework processes a rich set of profile characteristics, including account information, posting behavior, post sentiment, and network relationships, ensuring a multi-dimensional analysis of social media accounts. The hybrid architecture of DeepFakeGuard merges outputs from individual sub-models, which are then processed through dense layers for final classification using a sigmoid activation function. This multi-faceted approach significantly enhances detection accuracy, precision, and recall compared to traditional methods. The framework is highly scalable and adaptable to various social media platforms, offering a versatile tool for strengthening online security. With strong performance metrics, including high classification accuracy, DeepFakeGuard demonstrates its potential for real-world applications in mitigating the risks associated with fake profiles. By fostering secure and trustworthy social media environments, this research contributes to the ongoing fight against fraudulent accounts, paving the way for safer online interactions. © 2025 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Skin Cancer Classifier: Performance Enhancement Using Deep Learning Models

Skin Cancer Classifier: Performance Enhancement Using Deep L...

引用

International conference on Signal processing and communication (ICSC)

作者： Swati Mishra Megha Agarwal Department of Electronics and Communication Engineering Jaypee Institute of Information Technology Noida India

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

Skin cancer ranks among the most prevalent human malignancies, primarily diagnosed through visual methods, commencing with clinical screening, followed by dermoscopic analysis. The intricate alterations in the visual appearance of skin lesions pose a considerable challenge for automated classification through images. Deep learning techniques have been harnessed to support dermatologists in enhancing diagnostic accuracy. To address this, deep convolutional neural networks (CNNs) are employed to achieve highly discriminating and potentially generalizable results for image classification problems. This research introduces a prediction model designed to classify skin lesions into seven categories using the HAM10000 skin cancer dataset. The MobileNetV2, Resnet50, and DenseNet121 models were used in this study. The MobileNetV2 outperforms with 99.72 % accuracy and achieves 0.88, 0.89, and 0.88 values of precision, recall, and F1 score.

关键词： Deep learning visualization Analytical models Accuracy Computational modeling Skin Real-time systems Lesions Skin cancer Residual neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhanced Image Steganography Using Customized Differences between the Neighboring Pixels

Enhanced Image Steganography Using Customized Differences be...

引用

International conference on Signal processing and communication (ICSC)

作者： Maulana Alirridlo Adifa Widyadhani Chanda D'Layla Ntivuguruzwa Jean De La Croix Tohari Ahmad Departement of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia University of Rwanda Kigali Rwanda

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

In the digital era, safeguarding sensitive information from unauthorized access is paramount. Image steganography, which inconspicuously embeds data into visual media, has emerged as a promising solution. However, balancing data embedding capacity with image quality remains a challenge. This study introduces a novel steganographic method that optimizes visual fidelity and payload capacity by utilizing customized differences between neighboring pixels within grouped blocks. Experimental results demonstrate the effectiveness of the proposed method, achieving a Peak Signal-to-Noise Ratio (PSNR) of up to 48.99 dB and a Mean Squared Error (MSE) as low as 1.20 on complex images like “Baboon.” Additionally, Structural Similarity Index Measure (SSIM) values consistently reach a perfect 1.00 across several test cases. The method also achieves a significant payload increase, embedding up to 119,496 bits in the “Resolution Chart” image. By leveraging the precise control over pixel differences, this study introduces a new paradigm in steganography, addressing the trade-off between capacity and quality while ensuring imperceptibility and high efficiency.

关键词： Image quality Steganography visualization PSNR Measurement uncertainty information security Signal processing Media Indexes Payloads

来源：评论

学校读者我要写书评

暂无评论

I Hear, See, Speak & Do: Bringing Multimodal information processing to Intelligent Virtual Agents for Natural Human-AI communication

I Hear, See, Speak & Do: Bringing Multimodal Information Pro...

引用

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Ke Li Fariba Mostajeran Sebastian Rings Lucie Kruse Susanne Schmidt Michael Arz Erik Wolf Frank Steinicke Human-Computer Interaction University of Hamburg HIT Lab NZ University of Canterbury

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

In this demo paper, we present an Extended Reality (XR) framework providing a streamlined workflow for creating and interacting with intelligent virtual agents (ivAs) with multimodal information processing capabilities using commercially available artificial intelligence (AI) tools and cloud services such as large language and vision models. The system supports (i) the integration of high-quality, customizable virtual 3D human models for visual representations of ivAs and (ii) multimodal communication with generative AI-driven ivAs in immersive XR, featuring realistic human behavior simulations. Our demo showcases the enormous potential and vast design space of embodied ivAs for various XR applications.

关键词： Solid modeling visualization Three-dimensional displays Extended reality Metaverse information processing User interfaces Systems support Haptic interfaces Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Vision Transformers for Mpox Detection

Vision Transformers for Mpox Detection

引用

International conference on Artificial Intelligence in information and communication (ICAIIC)

作者： Gelan Ayana So-Yun Park Se-Woon Choe Medical IT Convergence Engineering Kumoh National Institute of Technology Gumi Republic of Korea IT Convergence Engineering Kumoh National Institute of Technology Gumi Republic of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

Monkeypox (Mpox) has emerged as a significant public health concern, with increasing cases reported worldwide. Accurate and timely diagnosis is crucial for effective treatment and containment. Traditional diagnostic methods, such as polymerase chain reaction, though reliable, are time-consuming and require specialized equipment. Image-based detection methods have gained attention as a complementary diagnostic tool. Conventional image-based methods rely heavily on convolutional neural networks (CNNs); however, vision transformers (ViTs) have emerged as a novel deep learning approach with potential benefits in medical imaging. CNN shave been the cornerstone of medical image analysis, but they come with limitations, particularly in handling complex and diverse visual data, whereas ViTs, originally designed for natural language processing, have shown remarkable potential in visual tasks due to their ability to capture long-range dependencies in images. This paper explores the use of ViTs, a novel deep learning architecture, in detecting Mpox. The study compares ViTs with existing CNN-based methods, evaluates their performance in detecting Mpox, and discusses the implications of their use in clinical settings. Our findings suggest that ViTs offer superior accuracy, making them a valuable tool in disease detection.

关键词： Computer vision visualization Accuracy Materials reliability Transformers Natural language processing Convolutional neural networks Polymers Public healthcare Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

A Proposed Model to Transliterate Digitalized Braille Text into Gujarati: An Aid for visually Challenged People

A Proposed Model to Transliterate Digitalized Braille Text i...

引用

3rd International conference on Advancements in Smart Computing and information Security, ASCIS 2024

作者： Jariwala, Nikisha Popat, Kalpesh Smt. Tanuben & Dr. Manubhai Trivedi College of Information Science Affiliated to Veer Narmad South Gujarat University Gujarat Surat India Faculty of Computer Applications Marwadi University Gujarat Rajkot India

ISBN: (纸本)9783031863011

information and communication Technology (ICT), in the modern digital era has become so cutting-edge and touched to each and every field but there is still a disconnect between visually impaired persons and communication technologies because of ignorance and inattention. Due to the limited availability of resources and tools;people with visual impairments are unable to communicate in writing. In this paper, researcher has tried to draw the attention towards the challenges that are faced by visually impaired individuals in written communication and also discussed the benefits of having a tool that eradicate the communication gap. To overcome the challenges faced by blind people;author has proposed a model based on Natural Language processing (NLP) and character mapping technique that act as an aid to transliterate the Braille text written by blind people to our regional language Gujarati. The technique used in the model uses standard Braille syntax. Rules are formed, lookup table is created, Braille characters are identified and they are transliterated to Gujarati language text. The model shows satisfactory result in the transliteration of Braille characters to Gujarati. It will also help visually impaired students in their education. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Braille text Character mapping Digital text processing Gujarati language Natural Language processing (NLP) Transliteration visually impaired people

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383页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：