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

25,249 篇 会议
280 篇 期刊文献
4 册 图书
3 篇 学位论文

馆藏范围

25,536 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

15,801 篇 工学
- 9,866 篇 计算机科学与技术...
- 6,079 篇 电气工程
- 5,768 篇 信息与通信工程
- 5,611 篇 软件工程
- 2,017 篇 光学工程
- 1,448 篇 控制科学与工程
- 1,280 篇 机械工程
- 1,153 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
- 794 篇 仪器科学与技术
- 261 篇 网络空间安全
- 253 篇 化学工程与技术
- 244 篇 安全科学与工程
- 238 篇 交通运输工程
- 183 篇 材料科学与工程（可...
- 164 篇 土木工程
- 161 篇 建筑学
5,714 篇 理学
- 3,481 篇 物理学
- 2,204 篇 数学
- 886 篇 生物学
- 563 篇 统计学（可授理学、...
- 420 篇 系统科学
- 310 篇 化学
3,021 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...
1,387 篇 管理学
- 849 篇 管理科学与工程(可...
- 610 篇 图书情报与档案管...
- 169 篇 工商管理
180 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

3,121 篇 image processing
2,084 篇 image coding
2,021 篇 visualization
1,752 篇 image segmentati...
1,488 篇 feature extracti...
1,082 篇 image reconstruc...
907 篇 cameras
885 篇 signal processin...
833 篇 image color anal...
756 篇 humans
714 篇 image edge detec...
688 篇 image enhancemen...
665 篇 computer vision
650 篇 training
582 篇 image analysis
568 篇 deep learning
536 篇 image quality
481 篇 conferences
473 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

24,726 篇 英文
489 篇 土耳其文
206 篇 其他
131 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 25536 条记录，以下是301-310 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：

LOFT: LATENT SPACE OPTIMIZATION AND GENERATOR FINE-TUNING FOR DEFENDING AGAINST DEEPFAKES 49

LOFT: LATENT SPACE OPTIMIZATION AND GENERATOR FINE-TUNING FO...

引用

49th ieee International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Zeng, Shaoyou Wang, Wenhao Huang, Fangjun Fang, Yanmei Sun Yat Sen Univ Sch Cyber Sci & Technol Shenzhen Campus Shenzhen Peoples R China

ISBN: (纸本)9798350344868;9798350344851

DeepFakes pose a significant threat to individual reputations and society as a whole. Existing proactive defense strategies concentrate on adding adversarial perturbations to images to disrupt or nullify the generation of DeepFakes, but these approaches are easily detectable by human perception and can be removed. To address this challenge, we propose a three-stage framework called LOFT (Latent Space Optimization and Generator Fine-Tuning for Defending against DeepFakes). First, encoding the original image into the latent space to obtain a latent code that captures facial features. Second, utilizing Adversarial Latent Optimization to optimize the latent code for reconstructing the image and defending against DeepFake manipulation. Third, fine-tuning the generator to enhance the reconstructed image's visual quality and defense capability further. Our study evaluates the effectiveness of our proposed framework through two distinct DeepFake tasks: attribute editing and face reenactment. Various experimental results demonstrate that our proposed framework outperforms the existing benchmark in both visual quality and defense capability.

关键词： DeepFake proactive defense adversarial attack latent representations image forensics

来源：评论

学校读者我要写书评

暂无评论

TOWARD SUFFICIENT SPATIAL-FREQUENCY INTERACTION FOR GRADIENT-AWARE UNDERWATER image ENHANCEMENT 49

TOWARD SUFFICIENT SPATIAL-FREQUENCY INTERACTION FOR GRADIENT...

引用

49th ieee International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Zhao, Chen Cai, Weiling Dong, Chenyu Zeng, Ziqi Nanjing Normal Univ Sch Artificial Intelligence Nanjing 210023 Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Underwater images suffer from complex and diverse degradation, which inevitably affects the performance of underwater visual tasks. However, most existing learning-based underwater image enhancement (UIE) methods mainly restore such degradations in the spatial domain, and rarely pay attention to the fourier frequency information. In this paper, we develop a novel UIE framework based on spatial-frequency interaction and gradient maps, namely SFGNet, which consists of two stages. Specifically, in the first stage, we propose a dense spatial-frequency fusion network (DSFFNet), mainly including our designed dense fourier fusion block and dense spatial fusion block, achieving sufficient spatial-frequency interaction by cross connections between these two blocks. In the second stage, we propose a gradient-aware corrector (GAC) to further enhance perceptual details and geometric structures of images by gradient map. Experimental results on two real-world underwater image datasets show that our approach can successfully enhance underwater images, and achieves competitive performance in visual quality improvement. The code is available at https://***/zhihefang/SFGNet.

关键词： Underwater image enhancement gradient map spatial-frequency interaction

来源：评论

学校读者我要写书评

暂无评论

PERCEPTION-ORIENTED OMNIDIRECTIONAL image SUPER-RESOLUTION BASED ON TRANSFORMER NETWORK 30

PERCEPTION-ORIENTED OMNIDIRECTIONAL IMAGE SUPER-RESOLUTION B...

引用

30th ieee International conference on image processing (ICIP)

作者： An, Hongyu Zhang, Xinfeng Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728198354

Omnidirectional image (ODI) super-resolution (SR) is an important technique in augmented reality and virtual reality applications to address the low-resolution problem caused by limitations in capturing devices or bandwidth. The ODI projection distortion makes it challenging to apply existing SR methods. In this paper, we propose an ODI SR method by leveraging the characteristics of ODIs and human visual characteristics. Specifically, we firstly design a perception-orientated adaptive loss function by jointly utilizing saliency map and latitude map. In our proposed ODI-SR network, we introduce an attention module to aggregate multi-scale information and leverage spherical convolution to adapt to the spheric format of ODIs. Furthermore, we design a data augmentation strategy for ODIs according to viewpoint distribution to further improve the visual quality of SR images. Extensive experimental results demonstrate that the proposed method achieves state-of-the-art performance according to both qualitative and quantitative evaluations.

关键词： Omnidirectional image super-resolution perceptual quality

来源：评论

学校读者我要写书评

暂无评论

Hybrid Feature Approach for Enhancing Zero-Shot image Classification 4th

Hybrid Feature Approach for Enhancing Zero-Shot Image Classi...

引用

4th International conference on Artificial Intelligence and Knowledge processing

作者： Khanam, Shaista Sonar, Poonam N. Mumbai Univ Mumbai Maharashtra India

ISBN: (纸本)9783031734762;9783031734779

Zero-shot learning (ZSL) directs the challenge of classifying unseen test images without explicit training on those samples. ZSL can identify and classify unlabeled images available in abundance by learning from visual and semantic embedding vectors (feature vectors). Information-enriched visual features extracted from images play a crucial role in ZSL. This paper proposes a hybrid feature approach that integrates low-level (LL), and high-level (HL) features extracted from images. Gray Level Co-occurrence Matrix (GLCM) and Gabor features are employed to obtain LL texture features, while HL features are derived from the ResNet-50 model, renowned for capturing complex hierarchical representations. These hybrid visual features are then mapped with semantic features using linear mapping, where the semantic features are embedding vectors of labels generated by the fastText model. Experiments on the AWA2 and SUN datasets are conducted in a bid to evaluate the proposed approach's effectiveness. The hybrid feature approach has demonstrated enhanced quality in zero-shot image classification, effectively classifying images that the model has not seen during training.

关键词： Hybrid feature Zero-shot image classification GLCM

来源：评论

学校读者我要写书评

暂无评论

Filling the Gap: Enhancing Ultra-Low Light image Brightness Through Multi-Band NIR Estimation

Filling the Gap: Enhancing Ultra-Low Light Image Brightness ...

引用

2023 ieee International conference on visual communications and image processing, VCIP 2023

作者： Park, Jeong-Hyeok Park, Tae-Sung Kim, Jong-Ok Korea University School of Electrical Engineering Seoul Korea Republic of

ISBN: (纸本)9798350359855

We propose a method for capturing high-quality images in low-light environments using multi-band near-infrared (NIR) images, which offer robustness to brightness variations and provide structural information not present in RGB images. As multi-band NIR images are not commonly available in consumer cameras, an RGB-NIR conversion network is employed to estimate them. Training data comes from a new low-light dataset with NIR-RGB image pairs. Unlike single-band approaches, this method utilizes multi-band NIR images with peak wavelengths of 785nm, 850nm, and 940nm, resulting in enhanced quality. Integration of the RGB-NIR conversion network into an existing low-light enhancement (LLIE) network is achieved using the proposed cross-attention transformer. Experimental results validate the effectiveness of multi-band NIR estimation in enhancing low-light intensity. Moreover, the proposed RGB-NIR conversion network and cross-attention module can be applied to any existing deep LLIE networks. © 2023 ieee.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Denoising Diffusion Adversarial Models for Unconditional Medical image Generation 31

Denoising Diffusion Adversarial Models for Unconditional Med...

引用

31st ieee conference on Signal processing and communications Applications (SIU)

作者： Dalmaz, Onat Saglam, Baturay Elmas, Gokberk Mirza, Muhammad Cukur, Tolga Bilkent Univ Elekt & Elekt Muhendisligi Bolumu Ankara Turkiye Bilkent Univ Ulusal Manyet Rezonans Arastirma Merkezi UMRAM Ankara Turkiye Bilkent Univ Sinirbilim Programi Muhendislik & Fen Bilimleri Enstitusu Ankara Turkiye

ISBN: (纸本)9798350343557

Unconditional medical image synthesis is the task of generating realistic and diverse medical images from random noise without any prior information or constraints. Synthesizing realistic medical images can enrich the quality and diversity of medical imaging datasets, which in turn, enhance the performance and generalization of deep learning models for medical imaging. Prevalent approach for synthesizing medical images involves generative adversarial networks (GAN) or denoising diffusion probabilistic models (DDPM). However, GAN models that implicitly learn the image distribution are prone to limited sample fidelity and diversity. On the other hand, diffusion models suffer from slow sampling speed due to small diffusion steps. In this paper, we propose a novel diffusion-based method for unconditional medical image synthesis, Diff-Med-Synth, that generates realistic and diverse medical images from random noise. Diff-Med-Synth combines the advantages of denoising diffusion probabilistic models and GANs to achieve fast and efficient image sampling. We evaluate our method on two multi-contrast MRI datasets and show that it outperforms state-of-the-art methods in terms of quality, diversity, and fidelity of the synthesized images.

关键词： denoising diffusion models generative modeling medical image synthesis unconditional generation adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Feature Decomposition and Attribute Augmentation for Attribute-based Person Search

Feature Decomposition and Attribute Augmentation for Attribu...

引用

2023 ieee International conference on visual communications and image processing, VCIP 2023

作者： Wang, Xin Liu, Fangfang Guo, Caili Li, Zheng Zhang, Hao Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350359855

The attribute-based person search task aims to find matching pedestrian images by text attributes, which is relevant in scenarios where no query image is given. However, the existing methods exhibit inferior performance due to their inadequate representation of local fine-grained features, which hinders their ability to effectively model intra-class variations. In addition, there is a zero-shot retrieval problem due to the large number of unseen categories in the test set, resulting in suboptimal generalization performance. In this paper, we propose a novel Feature Decomposition and Attribute Augmentation (FDAA) framework to solve the above problems. Firstly, by decomposing the global features of the image from different directions, the local features are extracted at multiple granularities, thus effectively improving the discrimination ability of the model. Secondly, an attribute augmentation strategy is proposed that can effectively expand the combination of attributes during training and improve the generalization ability of the model. Extensive experiments on the PETA, Market-1501 Attribute, and PA100K datasets demonstrate the effectiveness of our proposed method, outperforming state-of-the-art methods. © 2023 ieee.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

HISTOHDR-NET: HISTOGRAM EQUALIZATION FOR SINGLE LDR TO HDR image TRANSLATION 31

HISTOHDR-NET: HISTOGRAM EQUALIZATION FOR SINGLE LDR TO HDR I...

引用

2024 International conference on image processing

作者： Barua, Hrishav Bakul Krishnasamy, Ganesh Wong, KokSheik Dhall, Abhinav Stefanov, Kalin Monash Univ Malaysia Sch Informat Technol Subang Jaya Malaysia TCS Res Robot & Autonomous Syst Lab Kolkata India Flinders Univ S Australia Coll Sci & Engn Adelaide SA Australia Monash Univ Fac Informat Technol Clayton Vic Australia

ISBN: (纸本)9798350349405;9798350349399

High Dynamic Range (HDR) imaging aims to replicate the high visual quality and clarity of real-world scenes. Due to the high costs associated with HDR imaging, the literature offers various data-driven methods for HDR image reconstruction from Low Dynamic Range (LDR) counterparts. A common limitation of these approaches is missing details in regions of the reconstructed HDR images, which are overor under-exposed in the input LDR images. To this end, we propose a simple and effective method, HistoHDR-Net, to recover the fine details (e.g., color, contrast, saturation, and brightness) of HDR images via a fusion-based approach utilizing histogram-equalized LDR images along with self-attention guidance. Our experiments demonstrate the efficacy of the proposed approach over the state-of-art methods.

关键词： Data fusion Self-attention High dynamic range imaging Deep learning Histogram equalization

来源：评论

学校读者我要写书评

暂无评论

Foreground-Background Disentanglement based on image and Feature Co-Learning for 3D-Aware Generative Models

Foreground-Background Disentanglement based on Image and Fea...

引用

2023 ieee International conference on visual communications and image processing, VCIP 2023

作者： Lee, Sanghyuk Kim, Daeha Song, Byung Cheol Inha University Department of Electrical and Computer Engineering Incheon Korea Republic of

ISBN: (纸本)9798350359855

Recently, studies on generative models using 3D information are active. GIRAFFE, one of the latest 3D-aware generative models, shows better feature disentanglement than existing generative models because it generates an image through volume rendering of independently formed 3D neural feature fields. However, GIRAFFE still suffers from an issue where foreground and background disentanglement is not smooth. In order to accomplish better disentanglement performance than GIRAFFE, we propose co-adversarial learning of the generative model at both image- and feature-levels. As a result of rich simulation experiments, the proposed generative model can produce photo-realistic images with only fewer parameters than existing 3D-aware generative models, along with excellent foreground-background disentanglement performance. © 2023 ieee.

关键词： Volume rendering

来源：评论

学校读者我要写书评

暂无评论

Vision Language Models for Oil Palm Fresh Fruit Bunch Ripeness Classification 8

Vision Language Models for Oil Palm Fresh Fruit Bunch Ripene...

引用

ieee 8th International conference on Signal and image processing Applications (ieee ICSIPA)

作者： Goh, Jin Yu Yunos, Yusri Md Sheikh, Usman Ullah Ali, Mohamed Sultan Mohamed Univ Teknol Malaysia Fac Elect Engn Johor Baharu 81310 Johor Malaysia Qatar Univ Dept Elect Engn Coll Engn Doha Qatar

ISBN: (纸本)9798350352368

The accurate classification of fresh fruit bunch ripeness is crucial for optimizing oil quality and yield in the palm oil industry. Traditional manual inspection methods are labor-intensive, subjective, and prone to errors, motivating the exploration of automated solutions. This paper examined the potential of vision language models, including LLaVA 1.5, YiVL, and PaliGemma, to automate and enhance FFB ripeness assessment. The models were evaluated on their ability to classify ripeness stages and the accuracy of generated descriptive text using metrics like BLEU and ROUGE scores. Yi-VL achieved the highest descriptive accuracy with a ROUGE-L score of 93.14. However, it processes 0.18 samples per second, which is slower than PaliGemma (0.53 samples/second). PaliGemma is 194.44% more efficient in samples/second than Yi-VL, making it better suited for realtime applications despite its lower accuracy (ROUGE-L: 26.15). LLaVA 1.5 offers a balance between accuracy (ROUGE-L: 82.16) and efficiency (0.22 samples/second). This research highlighted the trade-offs between different VLMs for FFB ripeness assessment, demonstrating their potential to revolutionize the agriculture industry. Future work may focus on optimizing model performance and deploying these technologies in real-world scenarios.

关键词： FFB Large Language Models visual Question Answering Deep Learning image processing

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 << < 27 28 29 30 31 32 33 34 35 36 > >>

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：