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

87 篇 会议
1 册 图书

馆藏范围

88 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

57 篇 工学
- 43 篇 计算机科学与技术...
- 30 篇 软件工程
- 20 篇 光学工程
- 20 篇 信息与通信工程
- 17 篇 电气工程
- 12 篇 生物工程
- 11 篇 电子科学与技术（可...
- 10 篇 生物医学工程（可授...
- 7 篇 仪器科学与技术
- 4 篇 材料科学与工程（可...
- 4 篇 化学工程与技术
- 4 篇 安全科学与工程
- 2 篇 控制科学与工程
- 1 篇 动力工程及工程热...
- 1 篇 建筑学
- 1 篇 水利工程
40 篇 理学
- 22 篇 数学
- 15 篇 物理学
- 14 篇 生物学
- 5 篇 化学
- 5 篇 统计学（可授理学、...
- 2 篇 系统科学
- 1 篇 大气科学
7 篇 医学
- 7 篇 临床医学
- 4 篇 基础医学(可授医学...
- 3 篇 药学(可授医学、理...
- 2 篇 公共卫生与预防医...
5 篇 管理学
- 4 篇 图书情报与档案管...
- 2 篇 管理科学与工程(可...
2 篇 教育学
- 2 篇 教育学
1 篇 农学

主题

9 篇 image segmentati...
6 篇 signal processin...
5 篇 image enhancemen...
4 篇 deep learning
4 篇 neural networks
4 篇 encryption
4 篇 image recognitio...
3 篇 image fusion
3 篇 image edge detec...
3 篇 image processing
3 篇 feature extracti...
2 篇 knowledge engine...
2 篇 roads
2 篇 deep neural netw...
2 篇 magnetic resonan...
2 篇 safety
2 篇 software algorit...
2 篇 signal processin...
2 篇 ciphers
2 篇 image

机构

2 篇 highway developm...
2 篇 university of so...
2 篇 nmam institute o...
2 篇 state grid zheji...
2 篇 shri madhwa vadi...
2 篇 hangzhou e. ener...
2 篇 guangxi vocation...
1 篇 faculty of scien...
1 篇 university of no...
1 篇 department of el...
1 篇 humboldt univ de...
1 篇 inner mongolia u...
1 篇 school of biomed...
1 篇 network and data...
1 篇 dept of acse vig...
1 篇 northwest minzu ...
1 篇 sichuan universi...
1 篇 university of ku...
1 篇 ensit cerep tuni...
1 篇 college of compu...

作者

2 篇 ananth alaka
2 篇 bhat sachin s.
1 篇 wang yiming
1 篇 kyeong-seop kim
1 篇 najoua essoukri ...
1 篇 arun prasath t.
1 篇 feng liuping
1 篇 qianxu dong
1 篇 kim kee-deog
1 篇 liu lidong
1 篇 sudharani b.
1 篇 wajdi farhat
1 篇 liyun hua
1 篇 junyu cai
1 篇 i. r. farah
1 篇 huang rui
1 篇 chaouch asma
1 篇 eldeeb tarek
1 篇 li liang
1 篇 pareek piyush ku...

语言

88 篇 英文

检索条件"任意字段=2nd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2022"

共 88 条记录，以下是1-10 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：

Advancing Techniques for Deepfake Detection and Evaluation: Challenges and Innovations

Advancing Techniques for Deepfake Detection and Evaluation: ...

引用

Computational Intelligence, Communication Technology and Networking (CICTN), international conference on

作者： Pradum Kumar Singh Sourav Sharma Ritu Sachdeva School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

The proliferation of deepfakes-also termed artificial intelligence-generated synthetic media poses unprecedented challenges to the digital authenticity of media, for media integrity, and to societies’ trust in its credibility. Despite such significant technological advancements, current methodologies for detecting deepfakes remain somewhat fragmented, reactive, and often unable to keep pace with rapidly evolving technologies in generative AI. This article considers a comprehensive multi-modal approach toward deepfake detection by integrating an advanced machine learning algorithm, novel statistical correlation techniques, and forensic image analysis that would fill in the critical gaps in the existing frameworks. By using an extensive dataset of 10,000 synthetic and authentic media samples from diverse domains, we developed a hybrid neural network architecture that attained 94.3% accuracy on identifying AI-generated content. Our methodology utilized ensemble learning by combining spatial-temporal inconsistency detection, biological signal analysis, and advanced feature extraction algorithms. Key findings demonstrate significant vulnerabilities in current deepfake generation models, with our proposed technique successfully identifying subtle artifacts and inconsistencies across multiple generative AI platforms. This research conclusively demonstrates that proactive, adaptive detection strategies are critical to mitigating the potential risks associated with synthetic media, providing a robust framework for future technological interventions in digital forensics and media authentication.

关键词： Deepfakes Machine learning algorithms Generative AI Neural networks Digital forensics signal processing algorithms Authentication Media Feature extraction Information integrity

来源：评论

学校读者我要写书评

暂无评论

COVID-19 and Pneumonia Detection using X-ray image-Based Deep Learning Methods 2

COVID-19 and Pneumonia Detection using X-ray Image-Based Dee...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Li, Yuxiao McGill University Montreal Canada

ISBN: (纸本)9781510660571

Globally, pneumonia is the leading cause of death for young people and children. An X-ray of the chest is usually used to diagnose pneumonia by a trained specialist. However, the process is tedious and can result in disagreements among radiologists. It is possible to improve diagnostic accuracy through the use of computer-aided diagnostic systems. In this work, the ResNet model was selected to work as the covid-19 and pneumonia detector based on X-ray image. Several experiments are conducted on to achieve an optimal results. © 2022 SPIE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

The application of low rank matrix decomposition method in image restoration 2

The application of low rank matrix decomposition method in i...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Peng, Yue Northwest Minzu University China

ISBN: (纸本)9781510660571

image restoration is a hot issue in the field of image processing. Traditional algorithms approach the original function by a regular function or remove redundant noise by similarity. This process is complicated and cumbersome. In this paper, the low rank approximate matrix of the image matrix is equivalent to the product of two smaller matrices. At the same time, the first-order and second-order statistical information of the image matrix is effectively maintained by using the matrix Frobenius norm and matrix kernel normal. Secondly, the alternating direction multiplier method is utilized to solve the model. Finally, experimental results test the effectiveness of the proposed algorithm. © 2022 SPIE.

关键词： image reconstruction

来源：评论

学校读者我要写书评

暂无评论

The Effect of Data Augmentation and Depth of networks on CNN-based Breast X-ray image Diagnosis of Pneumonia 2

The Effect of Data Augmentation and Depth of networks on CNN...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Wang, Yiming Peking University No.5 Yiheyuan Road Haidian District Beijing China

ISBN: (纸本)9781510660571

COVID-19 has become a worldwide disease that draws researchersҠattention, and people have tried deep learning based methods to boost the diagnosis. It is crucial to design an algorithm for automatic Pneumonia Diagnosis. In this paper, we trained and applied a CNN-based model that is competent to not only diagnose COVID-19 based on breast x-ray images but also do classification on 4 classes, namely normal, COVID-19, viral pneumonia, and bacterial pneumonia. Further, we dive into the effect of data augmentation and depth of networks, and weӶe gained surprising results. © 2022 SPIE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Research on Fundus image Augmentation Algorithm 2

Research on Fundus Image Augmentation Algorithm

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Yu, Hui Cai, Lanlan Yan, Xue Network Information Center Wuhan University of Technology Wuhan430070 China School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan430070 China School of Computer and Artificial Intelligence Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781510660571

Diabetic retinopathy is a serious ocular complication caused by diabetes, has now become the main reason for the workforce blinding, using digital fundus image for diabetic retinopathy screening regularly is the key to preventing blindness. However, in the process of image acquisition, generation and transmission, it is susceptible to low light conditions and Gaussian noise, and it is difficult to detect small lesions and blood vessels in fundus images, which greatly reduces the accuracy of computer-aided diagnosis. Therefore, this paper proposes an image enhancement algorithm for digital fundus images, using adaptive clipping based on improved Canny edge detection to perform square clipping around fundus region. The improved CLAHE technique was used for low light enhancement to highlight the details of the lesions in the image. Aiming at the additive white Gaussian noise caused by medical image digitalize process, the fundus image denoising algorithm based on self-supervised EM-GMM is used to suppress the influence of noise by imposing sparsity constraint on covariance eigenvalues. The experiment shows that our methods achieve good performance in DDR dataset. © 2022 SPIE.

关键词： Computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

Fw-U-Net: a New Satellite image Segmentation of Forest and Water based on U-Net structure 2

Fw-U-Net: a New Satellite Image Segmentation of Forest and W...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Wang, Wentao Huang, Xuanyao Liu, Mingjie Chongqing University of Posts and Telecommunications No. 2 Chongwen Road CA Chong Qing China

ISBN: (纸本)9781510660571

As global environmental problems are becoming more and more serious, satellite image segmentation and automatic monitoring of forests and water bodies are becoming more and more important in order to prevent natural disasters and monitor natural conditions, including monitoring deforestation and areas affected by floods. In this paper, the traditional U-Net model is improved and a FW-U-Net model suitable for forest water segmentation is proposed. After verification, the segmentation verification scores of the forest coverage area and water area performance test set are 84.37%(83.65%) and 87.92%(85.42%) respectively, which has high accuracy and reference value for forest and water satellite image segmentation. © 2022 SPIE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Self-attention mechanism fusion method for bi-modal images 2

Self-attention mechanism fusion method for bi-modal images

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Junqing, Li Jiongyao, Ye School of Information Science and Engineering East China University of Science and Technology Shanghai200237 China

ISBN: (纸本)9781510660571

Multimodal information fusion can extract the important feature information of each modality and realize the information complementation between the modalities, which is a research direction of considerable interest at present. Extracting texture information from visible images and extracting typical features from infrared images are the main roles of dual-modal image fusion. To address the problems of information loss and low clarity of current deep learning-based fusion methods, this paper proposes a method to fuse bimodal images by embedding a network with attention mechanism. Due to the problems of low resolution and noise in infrared images, this method specifically uses encoder structures with different depths for infrared and visible images to extract shallow and deep features of each image, and then passes them through the attention-based fusion network to obtain the fused feature maps. A one-dimensional convolutional model based on a local cross-channel interaction mechanism without dimensionality reduction is used to construct the channel attention module in the fusion network, thus reducing the network complexity and improving the overall performance. The final fused image in this method relies on the decoder structure to generate. Experiments show that the method in this paper can fuse bimodal information better, and has some visual improvement under subjective evaluation compared with the comparison algorithm, and has 7.82%, 9.46%, 19.14% and 13.85% improvement in various objective evaluation indexes compared with DeepFuse, DenseFuse, FusionGAN and GANMcC respectively. © 2022 SPIE.

关键词： image fusion

来源：评论

学校读者我要写书评

暂无评论

Self2Align: A Self-Supervised Denoising Framework for Single-Scene images 2

Self2Align: A Self-Supervised Denoising Framework for Single...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Wang, Jian Heilongjiang University of Science and Technology Harbin China

ISBN: (纸本)9781510660571

In recent years, driven by the development of deep neural networks, image denoising technology has made great progress. One of the most representative technologies is the deep neural network denoiser based on supervised learning. The denoiser uses noise-clean image pairs as the input and output of a deep neural network, and trains the deep neural network to achieve the denoising goal. However, collecting many high-quality noise-clean image pairs is extremely challenging, which is mainly because (1) it is difficult to collect true and clean images;and (2) changes in motion and lighting make it impossible to align collected image pairs, which limits the widespread application of supervised learning denoising techniques. To solve the above problems, this paper proposes a simple and effective method Self2Align to train a deep neural network denoiser. First, we proposed an efficient deep network model for inter-image alignment. For the collection of original images, we only use noisy images and collected multiple images for different scenes. The trained alignment network was then used to align the original image pairs automatically. Second, the aligned image pairs generated in the first stage were used as training image pairs for the training of the denoising network. In addition, we introduced a new training strategy so that the network can obtain better performance. The proposed Self2Align architecture eliminates the reliance on noise-clean image pairs and reduces the acquisition difficulty of training image pairs in terms of self-supervised training of the network. We explained the feasibility of our proposed method through theoretical analysis and obtained competitive results through experimental verification. © 2022 SPIE.

关键词： image denoising

来源：评论

学校读者我要写书评

暂无评论

Second international conference on advanced algorithms and signal image processing, aasip 2022

Second International Conference on Advanced Algorithms and S...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

ISBN: (纸本)9781510660571

The proceedings contain 74 papers. The topics discussed include: design of muscle state sensing system based on flexible micro airbag structure;classification on normal chest x-ray and pneumonia x-ray;research and design of image super-resolution algorithm based on attention mechanism;automatic segmentation of thyroid nodule from ultrasound images using spatial-channel attentive u-net;research on line spectrum extraction based on improved discrete particle swarm;research on fundus image augmentation algorithm;human joint pose estimation based on the Kalman filter;self-attention mechanism fusion method for bi-modal images;and the application of low rank matrix decomposition method in image restoration.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved Least Significant Bit Algorithm based on RS-code 2

Improved Least Significant Bit Algorithm based on RS-code

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Xu, Jiamu University of Nottingham Electrical and Electronic Engineering NottinghamNG7 2RD United Kingdom

ISBN: (纸本)9781510660571

As a widely applied data hiding method, least significant bit (LSB) algorithm, is a spatial steganography which uses the lowest bits of each pixel's grayscale value to hide messages. In spite of its high capacitance, high load rate and imperceptibility is remarkable, the lack of robustness is the fatal problem which prevents the LSB algorithm's further application. This paper proposes a new high-robustness LSB method based on the Reed-Solomon (RS) code, and provides higher immunity of attack with slight cost of imperceptibility and capacity. This algorithm exploits the considerable error correction ability of RS-code to encode the watermark message before embedding them to the carrier image. Despite the size of the encoded message increases times to the original, this method makes self-correction of encrypted images feasible, which would provide more superiority among the algorithms that require carrier image as reference to extract watermark message. This paper provides the testing results of the LSB algorithm based on RS-code in Matlab, and verifies the immunity of both the proposed method and original method against noise and rotation attack, and finally determines that this algorithm is able to substantially enhance the robustness of encrypted image under a certain range of noise density. © 2022 SPIE.

关键词： Steganography

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9页 << < 1 2 3 4 5 6 7 8 9 > >>

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：