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

13,827 篇 会议
850 篇 期刊文献
31 册 图书
29 篇 学位论文
3 篇 专利

馆藏范围

14,739 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

7,760 篇 工学
- 4,047 篇 计算机科学与技术...
- 2,267 篇 电气工程
- 2,006 篇 软件工程
- 1,247 篇 生物医学工程（可授...
- 1,052 篇 信息与通信工程
- 987 篇 光学工程
- 654 篇 控制科学与工程
- 639 篇 仪器科学与技术
- 626 篇 核科学与技术
- 570 篇 机械工程
- 435 篇 电子科学与技术（可...
- 401 篇 生物工程
- 237 篇 测绘科学与技术
- 151 篇 材料科学与工程（可...
- 118 篇 航空宇航科学与技...
- 112 篇 建筑学
- 112 篇 土木工程
3,755 篇 理学
- 2,647 篇 物理学
- 1,104 篇 数学
- 469 篇 生物学
- 318 篇 统计学（可授理学、...
- 180 篇 化学
- 164 篇 系统科学
2,603 篇 医学
- 1,600 篇 临床医学
- 1,245 篇 特种医学
- 254 篇 基础医学(可授医学...
- 109 篇 医学技术（可授医学...
- 108 篇 药学(可授医学、理...
394 篇 管理学
- 272 篇 管理科学与工程(可...
- 138 篇 图书情报与档案管...
72 篇 农学
37 篇 艺术学
35 篇 法学
22 篇 经济学
21 篇 教育学
21 篇 文学
13 篇 军事学
3 篇 历史学

主题

7,672 篇 image reconstruc...
1,030 篇 cameras
871 篇 three-dimensiona...
782 篇 computed tomogra...
713 篇 image segmentati...
619 篇 reconstruction a...
606 篇 positron emissio...
561 篇 surface reconstr...
547 篇 shape
516 篇 image resolution
463 篇 magnetic resonan...
463 篇 training
455 篇 data mining
375 篇 imaging phantoms
363 篇 detectors
354 篇 deep learning
354 篇 image coding
346 篇 solid modeling
333 篇 attenuation
332 篇 compressed sensi...

机构

89 篇 univ chicago dep...
33 篇 department of ra...
32 篇 tsinghua univ de...
29 篇 department of ra...
28 篇 department of ra...
24 篇 suny stony brook...
22 篇 dartmouth coll t...
21 篇 microsoft resear...
21 篇 department of en...
20 篇 univ chinese aca...
17 篇 washington univ ...
17 篇 univ chicago dep...
16 篇 shanghai jiao to...
15 篇 university of sc...
15 篇 institute of nuc...
15 篇 university of ch...
14 篇 department of ra...
14 篇 tsinghua univ mi...
14 篇 department of ra...
14 篇 peng cheng lab p...

作者

82 篇 pan xiaochuan
31 篇 xia dan
25 篇 kudo hiroyuki
25 篇 liang zhengrong
25 篇 emil y. sidky
24 篇 m. defrise
23 篇 li zhang
23 篇 m.a. king
20 篇 zhengrong liang
20 篇 maier andreas
20 篇 ma jianhua
19 篇 kris thielemans
18 篇 yuxiang xing
18 篇 j.a. fessler
18 篇 g.t. gullberg
17 篇 grant t. gullber...
17 篇 liu yan
17 篇 chen guang-hong
16 篇 li liang
16 篇 hutton brian f.

语言

14,465 篇 英文
145 篇 其他
121 篇 中文
11 篇 土耳其文
2 篇 德文
2 篇 俄文
1 篇 法文
1 篇 日文
1 篇 泰文
1 篇 乌克兰文

检索条件"任意字段=Conference on Image Reconstruction from Incomplete Data"

共 14740 条记录，以下是191-200 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：

ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfer

ROSA: Reconstructing Object Shape and Appearance Textures by...

引用

IEEE Workshop on Applications of Computer Vision (WACV)

作者： Julian Kaltheuner Patrick Stotko Reinhard Klein University of Bonn

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Reconstructing an object's shape and appearance in terms of a mesh textured by a spatially-varying bidirectional reflectance distribution function (SVBRDF) from a limited set of images captured under collocated light is an ill-posed problem. Previous state-of-the-art approaches either aim to reconstruct the appearance directly on the geometry or additionally use texture normals as part of the appearance features. However, this requires detailed but inefficiently large meshes, that would have to be simplified in a post-processing step, or suffers from well-known limitations of normal maps such as missing shadows or incorrect silhouettes. Another limiting factor is the fixed and typically low resolution of the texture estimation resulting in loss of important surface details. To overcome these problems, we present ROSA, an inverse rendering method that directly optimizes mesh geometry with spatially adaptive mesh resolution solely based on the image data. In particular, we refine the mesh and locally condition the surface smoothness based on the estimated normal texture and mesh curvature. In addition, we enable the reconstruction of fine appearance details in high-resolution textures through a pioneering tile-based method that operates on a single pre-trained decoder network but is not limited by the network output resolution.

关键词： Geometry Adaptation models Surface reconstruction Shape Stability criteria Rendering (computer graphics) Decoding Surface texture Spatial resolution image reconstruction

来源：评论

学校读者我要写书评

暂无评论

On-the-fly image Compression Using Overfitted Shallow CNN Autoencoders

On-the-fly Image Compression Using Overfitted Shallow CNN Au...

引用

International image Processing, Applications and Systems conference (IPAS)

作者： John El Gallab Abdelwahab Ganna Abdallah Kassem Hend Makram Martina Muawad Mina Mikhael Tamer ElBatt Computer Science and Engineering The American University in Cairo Cairo Egypt

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

In the era of pervasive Internet use, managing large volumes of image data becomes crucial. To mitigate storage and bandwidth costs, image compression plays a pivotal role. Traditional image compression techniques like JPEG and PNG, while widely used, may suffer from limited compression rates. In this work, we propose a novel approach using shallow Convolutional Neural Network (CNN) autoencoders for on-the-fly image compression. Our model aims to achieve high compression rates with improved image quality compared to classical methods. Additionally, it supports decompression on the CPU in realtime, making no assumptions about client-side computational resources. We present a comprehensive methodology, including architecture design, experiments, and performance metrics. Our results demonstrate the effectiveness of the proposed approach, providing a competitive alternative for online content compression and decompression that outperforms JPEG in image quality assessment metrics at 33% compression rate. We also outperform other Learned image Compression (LIC) techniques in both the decompression time and number of trainable parameters with an improvement in the order of 10-times.

关键词： Measurement image quality image coding Autoencoders Transform coding Bandwidth Internet Convolutional neural networks Time factors image reconstruction

来源：评论

学校读者我要写书评

暂无评论

46th Annual conference of the German Association for Pattern Recognition, DAGM-GCPR 2024

46th Annual Conference of the German Association for Pattern...

引用

46th Annual conference of the German Association for Pattern Recognition, DAGM-GCPR 2024

ISBN: (纸本)9783031851865

The proceedings contain 22 papers. The special focus in this conference is on German Association for Pattern Recognition. The topics include: Self-supervised Semantic Segmentation from Audio-Visual data;BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation;fullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks;self-masking Networks for Unsupervised Adaptation;a Theoretical Formulation on the Use of Multiple Positive Views in Contrastive Learning;decoupling of Neural Network Calibration Measures;examining Common Paradigms in Multi-task Learning;DIAGen: Semantically Diverse image Augmentation with Generative Models for Few-Shot Learning;efficient and Discriminative image Feature Extraction for Universal image Retrieval;anomaly Detection with Conditioned Denoising Diffusion Models;surgeoNet: Realtime 3D Pose Estimation of Articulated Surgical Instruments from Stereo images Using a Synthetically-Trained Network;Foundation Models Permit Retinal Layer Segmentation Across OCT Devices;correlation Clustering of Organoid images;animal Identification with Independent Foreground and Background Modeling;robust Tumor Segmentation with Hyperspectral Imaging and Graph Neural Networks;bigger Isn’t Always Better: Towards a General Prior for Medical image reconstruction;latent Diffusion Counterfactual Explanations;enhancing Surface Neural Implicits with Curvature-Guided Sampling and Uncertainty-Augmented Representations;uncertainty Voting Ensemble for Imbalanced Deep Regression;analytical Uncertainty-Based Loss Weighting in Multi-task Learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

46th Annual conference of the German Association for Pattern Recognition, DAGM-GCPR 2024

46th Annual Conference of the German Association for Pattern...

引用

46th Annual conference of the German Association for Pattern Recognition, DAGM-GCPR 2024

ISBN: (纸本)9783031851803

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dual-energy CT metal artifact reduction by combined material decomposition and projection domain threshold segmentation

Dual-energy CT metal artifact reduction by combined material...

引用

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

作者： Kai Chen Tianling Lyu Jean-Louis Coatrieux Yang Chen Nanjing University Of Posts And Telecommunications Southeast University Nanjing China Zhejiang Lab Hangzhou China Laboratoire Traitement du Signal et de l’Image Rennes France

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Dual-energy CT exploits the different attenuation characteristics of substances under different energy X-rays and collects high- and low-energy data from the same area to differentiate and quantify specific substances, which is now widely used in clinical diagnosis, disease monitoring, and other fields. If the object scanned during dual-energy CT imaging contains metallic material, the reconstructed image will suffer from metal artifacts. Metal artifacts in dual-energy CT result in surrounding tissue structures presenting erroneous CT values, blurred image details, and unclear border demarcation lines, which seriously affects the quality of the images as well as the accuracy of clinical diagnosis. To reduce metal artifacts in dual-energy CT, we combine material decomposition techniques with metal artifact reduction to explore metal artifact reduction methods applied to dual-energy CT.

关键词： Computed tomography Metallic materials Metals Imaging X-rays Signal processing Clinical diagnosis Speech processing image reconstruction Monitoring

来源：评论

学校读者我要写书评

暂无评论

CLEAR: Colon Segmentation with Liquid Error Avoidance and Refinement for VR Colonography

CLEAR: Colon Segmentation with Liquid Error Avoidance and Re...

引用

2025 IEEE conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2025

作者： Freire, Pedro Silva MacIel, Anderson Pereira, João Madeiras Jorge, Joaquim Moreira, Catarina Universidade de Lisboa INESC-ID Instituto Superior Técnico Portugal INESC-ID Data Science Institute Portugal University of Technology Sydney Australia

ISBN: (纸本)9798331514846

Colon cancer remains a leading cause of cancer-related deaths, emphasizing the importance of early detection and accurate diagnostics. While colonoscopy is the gold standard, its invasiveness deters frequent, widespread use. Desktop colonography offers a less invasive alternative, and Immersive Colonography improves the efficiency of the analysis. However, colonography requires anatomical reconstruction from CTs, and liquid pockets in CT colonography often obscure the colon, necessitating dual-position scans and doubling radiation exposure. We introduce an automatic segmentation method that integrates liquid regions to eliminate the need for a second CT scan. By requiring only one CT image, this approach enhances patient safety and comfort while maintaining accurate segmentation. The proposed method uses advanced filtering and geometry-based techniques to accurately segment air and liquid pockets, ensuring continuity in colon reconstructions. This innovation promises safer, more efficient VR colonography and improved diagnostic capabilities. © 2025 IEEE.

关键词： Colon Segmentation Colonography Medical Imaging

来源：评论

学校读者我要写书评

暂无评论

Efficient Low-Light image Enhancement Algorithm Based on Convolutional Neural Network and Local Pattern

Efficient Low-Light Image Enhancement Algorithm Based on Con...

引用

Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International conference on

作者： Wei Luo Chongqing Three Gorges Vocational College Chongqing Wanzhou China

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

With the widespread application of vision-assisted analysis models, how to enhance images and optimize details in low-light conditions is an important research direction. In view of the limitations of existing algorithms (low accuracy, high complexity, etc.), this paper proposes a new efficient low-light image enhancement algorithm based on the convolutional neural networks and local patterns. The proposed algorithm first combines the “S-shaped” illumination reliability mask curve with the local binary pattern (LBP) framework to model the image, which is used to solve the challenges of image noise, overexposure and color loss caused by the inconsistent local illumination. At the same time, the differentiable color histogram module is introduced to divide the image granularity and combined with dilated convolution to optimize feature extraction. The multi-scale semantic information extraction capability is enhanced through parallel multi-scale feature sampling blocks. The image super-resolution reconstruction model is then integrated into the enhancement process, and the enhancement task is innovatively completed from multiple perspectives. In the experiment, a comprehensive test was conducted on a data-set of 1,823,712 low-light images, and histogram equalization was used to compare with the traditional convolutional neural network algorithm. The test shows that the proposed method is superior to the comparison method in terms of enhancing image contrast, brightness consistency and detail retention.

关键词： Histograms image color analysis Superresolution Semantics Lighting Feature extraction Convolutional neural networks Reliability Colored noise image enhancement

来源：评论

学校读者我要写书评

暂无评论

Proceedings of SPIE -image reconstruction from incomplete data IV

Proceedings of SPIE -Image Reconstruction from Incomplete Da...

引用

image reconstruction from incomplete data IV

ISBN: (纸本)0819463957

The proceedings contain 20 papers. The topics discussed include: turbulence profiling using extended objects for slope detection and ranging (SLODAR);mitigating atmospheric effects in high-resolution infrared surveillance imagery with bispectral speckle imaging;restoration of nonuniformly wrapped images using accurate frame by frame shiftmap accumulation;three-dimensional image reconstruction in variable density acoustic tomography;imaging with singular electromagnetic beam;comparative study of projection/back-projection schemes in cryo-EM tomography;intensity diffraction tomography with a novel scanning protocol;quantifying and correcting motion artifacts in MRI;the optimal reconstruction from blurred and nonuniformly sampled data based on the optimum discrete approximation minimizing various worst-case measures of error;and analysis of gravel river beds using three-dimensional laser scanning.

关键词： image reconstruction

来源：评论

学校读者我要写书评

暂无评论

WebCode2M: A Real-World dataset for Code Generation from Webpage Designs 34

WebCode2M: A Real-World Dataset for Code Generation from Web...

引用

34th ACM Web conference, WWW 2025

作者： Gui, Yi Li, Zhen Wan, Yao Shi, Yemin Zhang, Hongyu Su, Yi Chen, Bohua Chen, Dongping Wu, Siyuan Zhou, Xing Jiang, Wenbin Jin, Hai Zhang, Xiangliang Huazhong University of Science and Technology Wuhan China Peking University Beijing China Chongqing University Chongqing China Hubei University of Automotive Technology Shiyan China Rabbitpre AI Shenzhen China University of Notre Dame Notre Dame United States National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster Grid Computing Lab School of Computer Science and Technology China

ISBN: (纸本)9798400712746

Automatically generating webpage code from webpage designs can significantly reduce the workload of front-end developers, and recent Multimodal Large Language Models (MLLMs) have shown promising potential in this area. However, our investigation reveals that most existing MLLMs are constrained by the absence of high-quality, large-scale, real-world datasets, resulting in inadequate performance in automated webpage code generation. To fill this gap, this paper introduces WebCode2M, a new dataset comprising 2.56 million instances, each containing a design image along with the corresponding webpage code and layout details. Sourced from real-world web resources, WebCode2M offers a rich and valuable dataset for webpage code generation across a variety of applications. The dataset quality is ensured by a scoring model that filters out instances with aesthetic deficiencies or other incomplete elements. To validate the effectiveness of WebCode2M, we introduce a baseline model based on the Vision Transformer (ViT), named WebCoder, and establish a benchmark for fair comparison. Additionally, we introduce a new metric, TreeBLEU, to measure the structural hierarchy recall. The benchmarking results demonstrate that our dataset significantly improves the ability of MLLMs to generate code from webpage designs, confirming its effectiveness and usability for future applications in front-end design tools. Finally, we highlight several practical challenges introduced by our dataset, calling for further research. © 2025 Copyright held by the owner/author(s).

关键词： Code Generation dataset Design to Code UI Automation

来源：评论

学校读者我要写书评

暂无评论

On the Design of Weakly-Convex Regularizers for Solving Linear Inverse Problems

On the Design of Weakly-Convex Regularizers for Solving Line...

引用

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

作者： Abijith Jagannath Kamath Abhishek Shreekant Bhandiwad Chandra Sekhar Seelamantula Department of Electrical Engineering Indian Institute of Science Bengaluru India

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Linear inverse problems are ubiquitous in signal processing and computational imaging. The prototypical problem is to recover a signal from noisy linear measurements. A typical optimization-based approach is to minimize the sum of a data-fidelity loss and a regularization function. The data-fidelity function ensures consistency with the measurements and the regularization function imparts desired properties to the solution. Convex regularization functions are typically preferred as one can provide theoretical guarantees. However, the convex-nonconvex (CNC) framework, which employs a convex data-fidelity loss and a nonconvex regularization function has been shown to be superior in terms of the quality of signal recovery. In this paper, we consider model-based and data-driven nonconvex regularization objectives to solve linear inverse problems. We consider the denoising problem and propose a constructive approach to design weakly convex regularization functions by minimizing a measure of maximum concavity. Our design approach captures known model-based regularization functions, including those that promote sparsity, and also includes learnable convolutional neural networks. Minimization of the objective follows first-order gradient-based methods. Our approach ensures that the overall reconstruction technique is provably convergent. We show that it outperforms state-of-the-art model-based techniques and is comparable to the benchmark learningbased methods. Crucially, our technique results in reconstructions with fewer artifacts compared to the state-of-the-art learning-based methods. Our reconstruction approach reduces the number of network parameters to be learnt for similar neural network architectures making it easier/faster to train.

关键词： Inverse problems Noise reduction Neural networks Prototypes Benchmark testing Convex functions Convolutional neural networks Noise measurement Speech processing image reconstruction

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 << < 16 17 18 19 20 21 22 23 24 25 > >>

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：