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

1,498 篇 会议
42 篇 期刊文献
3 篇 学位论文
1 册 图书

馆藏范围

1,544 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,150 篇 工学
- 753 篇 计算机科学与技术...
- 416 篇 软件工程
- 318 篇 测绘科学与技术
- 203 篇 建筑学
- 168 篇 光学工程
- 120 篇 土木工程
- 106 篇 电气工程
- 65 篇 信息与通信工程
- 65 篇 控制科学与工程
- 65 篇 生物医学工程（可授...
- 53 篇 机械工程
- 41 篇 生物工程
- 36 篇 材料科学与工程（可...
- 27 篇 仪器科学与技术
- 26 篇 化学工程与技术
- 23 篇 电子科学与技术（可...
492 篇 理学
- 222 篇 地理学
- 133 篇 物理学
- 94 篇 数学
- 48 篇 生物学
- 26 篇 化学
- 17 篇 地质学
427 篇 医学
- 398 篇 临床医学
- 33 篇 基础医学(可授医学...
- 28 篇 特种医学
- 18 篇 药学(可授医学、理...
100 篇 管理学
- 54 篇 管理科学与工程(可...
- 44 篇 图书情报与档案管...
56 篇 历史学
- 55 篇 考古学
19 篇 法学
- 19 篇 社会学
12 篇 教育学
11 篇 农学
5 篇 经济学
2 篇 文学
2 篇 军事学
1 篇 艺术学

主题

200 篇 virtual reality
154 篇 visualization
154 篇 image reconstruc...
133 篇 three-dimensiona...
109 篇 3d reconstructio...
90 篇 solid modeling
88 篇 cultural heritag...
87 篇 photogrammetry
62 篇 cameras
58 篇 augmented realit...
58 篇 surface reconstr...
51 篇 3d modelling
50 篇 3d modeling
47 篇 shape
44 篇 laser scanning
37 篇 data visualizati...
35 篇 geometry
34 篇 image segmentati...
34 篇 layout
33 篇 reconstruction

机构

14 篇 beihang univ sta...
14 篇 state key labora...
8 篇 univ debrecen fa...
6 篇 bruno kessler fd...
6 篇 beihang univ qin...
5 篇 trento
5 篇 kazimierz wielki...
5 篇 university of to...
4 篇 univ toronto on
4 篇 hajdusagi museum...
4 篇 beijing normal u...
4 篇 univ salamanca h...
4 篇 politecn milan d...
4 篇 tianjin univ tec...
4 篇 beihang universi...
4 篇 bruno kessler fd...
4 篇 univ palermo dep...
4 篇 univ ferrara dep...
3 篇 shanghai jiao to...
3 篇 shanghai ai lab

作者

22 篇 remondino f.
15 篇 barazzetti l.
14 篇 georgopoulos a.
10 篇 fassi f.
10 篇 qi yue
9 篇 previtali m.
8 篇 gilanyi attila
8 篇 yue qi
8 篇 scaioni m.
8 篇 roncoroni f.
7 篇 menna f.
7 篇 grussenmeyer p.
7 篇 luo xun
7 篇 adami a.
6 篇 tucci g.
6 篇 chmielewska kata...
6 篇 remondino fabio
5 篇 zhu yunrui
5 篇 agrafiotis p.
5 篇 achille c.

语言

1,521 篇 英文
17 篇 其他
4 篇 中文
3 篇 西班牙文

检索条件"任意字段=Conference on 3D Virtual Reconstruction and Visualization of Complex Architectures"

共 1544 条记录，以下是261-270 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：

HdF-SegNet: dynamic Integration of Hierarchical Information for Cardiac Magnetic Resonance Image Segmentation 21st

HDF-SegNet: Dynamic Integration of Hierarchical Information...

引用

21st Pacific Rim International conference on Artificial Intelligence, PRICAI 2024

作者： Wang, Zijuan Chen, Yucheng Mu, Nan Li, Xiaoning College of Computer Science Sichuan Normal University Chengdu China Department of Cardiology West China Hospital Sichuan University Chengdu China

ISBN: (纸本)9789819601271

Cardiac Magnetic Resonance Imaging (CMRI) presents complex morphological features in 3d space due to different cardiac cycles, respiratory motions and individual differences, with diverse variations in global morphology and local details between slices, which requires segmentation models to have accurate detail capturing and boundary recognition capabilities. In recent years, deep learning methods based on traditional Convolution Neural Network, such as U-Net architectures, use fixed-size convolution kernels, which are difficult to adapt to the complex deformation of the heart structure. In this paper, we propose a hierarchical dynamic fusion segmentation network (HdF-SegNet) with a two-branch architecture by combining deformable convolutions that can generate corresponding sensory field shapes according to the target deformation. In it, the upper branch reconstructs the original image and generates a priori information and local features to guide segmentation. The lower branch uses dynamic Large Kernel(dLK) to model the global information. We use the Feature Interweaving Module(FIM) to refine the different layers of features and fuse all the features after selecting them dynamically by channel and spatially. We experimented on the publicly available ACdC cardiac dataset with an average dice coefficient of 91.86%, the comparison experiments validate the superiority of HdF-SegNet on the task of CMRI segmentation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

ditto: Building digital Twins of Articulated Objects from Interaction

Ditto: Building Digital Twins of Articulated Objects from In...

引用

IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Jiang, Zhenyu Hsu, Cheng-Chun Zhu, Yuke Univ Texas Austin Dept Comp Sci Austin TX 78712 USA

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

digitizing physical objects into the virtual world has the potential to unlock new research and applications in embodied AI and mixed reality. This work focuses on recreating interactive digital twins of real-world articulated objects, which can be directly imported into virtual environments. We introduce ditto to learn articulation model estimation and 3d geometry reconstruction of an articulated object through interactive perception. Given a pair of visual observations of an articulated object before and after interaction, ditto reconstructs part-level geometry and estimates the articulation model of the object. We employ implicit neural representations for joint geometry and articulation modeling. Our experiments show that ditto effectively builds digital twins of articulated objects in a category-agnostic way. We also apply ditto to real-world objects and deploy the recreated digital twins in physical simulation. Code and additional results are available at https://***/ditto/

关键词： Geometry visualization Solid modeling Three-dimensional displays Buildings Estimation virtual environments

来源：评论

学校读者我要写书评

暂无评论

2nd International conference on Big data, IoT and Machine Learning, BIM 2023

2nd International Conference on Big Data, IoT and Machine Le...

引用

2nd International conference on Big data, IoT and Machine Learning, BIM 2023

ISBN: (纸本)9789819989362

The proceedings contain 69 papers. The special focus in this conference is on Big data, IoT and Machine Learning. The topics include: Phylogeny reconstruction Using k-mer derived Transition Features;developing an Interpretable Machine Learning Model for divorce Prediction;riot Perception and Safety Navigation of Autonomous Vehicles Using deep Learning;An Explainable AI Enable Approach to Reveal Feature Influences on Social Media Customer Purchase decisions;Field Programmable Gate Array in dNA Computing;XAI-driven Model Explainability and Prediction of P2P Bank Loan default Network;design Implication of a Compact-Sized, Low-Fidelity Rover for Tough Terrain Exploration;VioNet: An Enhanced Violence detection Approach for Videos Using a Fusion Model of Vision Transformer with Bi-LSTM and 3d Convolutional Neural Networks;rank Your Summaries: Enhancing Bengali Text Summarization Via Ranking-Based Approach;an Efficient Machine Learning Classification Model for Rainfall Prediction in Bangladesh;study on the Analysis and Prediction of drug Addiction Among University Students of Bangladesh Using Machine Learning;A deep CNN-Based Approach for Revolutionizing Bengali Handwritten Numeral Recognition;performance Analysis of Multiple deep Learning Models for Image Retrieval Problems;Advancing Lung Cancer diagnosis Through deep Learning and Grad-CAM-Based visualization Techniques;a Novel Approach to detect Stroke from 2d Images Using deep Learning;Enhancing Pneumonia diagnosis: An Ensemble of deep CNN architectures for Accurate Chest X-Ray Image Analysis;dataset for Road Roughness Assessment Using Image Classification Techniques and deep Learning Models: A Case Study on Bangladeshi National Highways;Noise-Aware-Based Texture descriptor, Evaluation Adjacent distance Local Ternary Pattern EAdLTP for Image Classification.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Generating Look-Alike Avatars: Perception of Head Shape, Texture Fidelity and Head Orientation of Another User's Look-Alike Avatar

Generating Look-Alike Avatars: Perception of Head Shape, Tex...

引用

virtual Reality and 3d User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Kwame Agyemang Baffour Oyewole Oyekoya CUNY Graduate Center University of Energy & Natural Resources Hunter College City University of New York

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

Using photorealistic look-alike avatars may enhance the likeability and realism of avatars in collaborative virtual environments. This research seeks to determine the influence of head shape, texture fidelity and head orientation of a look-alike avatar on perception of likeability and visual realism, especially when judged by other people. Two textured look-alike avatars were generated using: (i) three-dimensional (3d) stereophotogrammetry; and (ii) 3d face reconstruction from a single full-face image. Participants compared three different head orientations (0°, 45°, 90°) of the look-alike avatars' textured heads to their corresponding head silhouettes, to emphasize the differences in head shapes. Results suggest that participants prefer geometrically accurate photorealistic avatars of other people due to the accuracy of the head shape and texture fidelity. Participants ranked the likeability and realism of the look-alike avatars similarly regardless of the head orientation.

关键词： visualization Head Three-dimensional displays Shape Avatars conferences virtual environments

来源：评论

学校读者我要写书评

暂无评论

A truth-based primal-dual learning approach to reconstruct CT images utilizing the virtual imaging trial platform

A truth-based primal-dual learning approach to reconstruct C...

引用

conference on Medical Imaging - Physics of Medical Imaging

作者： Zarei, Mojtaba Sotoudeh-Paima, Saman Abadi, Ehsan Samei, Ehsan Duke Univ Ctr Virtual Imaging Trials Carl E Ravin Adv Imaging Labs Dept RadiolSch Med Durham NC 27706 USA Duke Univ Dept Elect & Comp Engn Pratt Sch Engn Durham NC 27706 USA

ISBN: (数字)9781510649385

ISBN: (纸本)9781510649385;9781510649378

Inherent to Computed tomography (CT) is image reconstruction, constructing 3d voxel values from noisy projection data. Modeling this inverse operation is not straightforward. Given the ill-posed nature of inverse problem in CT reconstruction, data-driven methods need regularization to enhance the accuracy of the reconstructed images. Besides, generalization of the results hinges upon the availability of large training datasets with access to ground truth. This paper offers a new strategy to reconstruct CT images with the advantage of ground truth accessible through a virtual imaging trial (VIT) platform. A learned primal-dual deep neural network (LPd-dNN) employed the forward model and its adjoint as a surrogate of the imaging's geometry and physics. VIT offered simulated CT projections paired with ground truth labels from anthropomorphic human models without image noise and resolution degradation. The models included a library of anthropomorphic, computational patient models (XCAT). The dukeSim simulator was utilized to form realistic projection data emulating the impact of the physics and geometry of a commercial-equivalent CT scanner. The resultant noisy sinogram data associated with each slice was thus generated for training. Corresponding linear attenuation coefficients of phantoms' materials at the effective energy of the x-ray spectrum were used as the ground truth labels. The LPd-dNN was deployed to learn the complex operators and hyper-parameters in the proximal primal-dual optimization The obtained validation results showed a 12% normalized root mean square error with respect to the ground truth labels, a peak signal-to-noise ratio of 32 dB, a signal-to-noise ratio of 1.5, and a structural similarity index of 96%. These results were highly favorable compared to standard filtered-back projection reconstruction (65%, 17 dB, 1.0, 26%).

关键词： Signal attenuation reconstruction algorithms Network architectures Signal to noise ratio Computed tomography Inverse problems X-ray computed tomography CT reconstruction Neural networks Sensors

来源：评论

学校读者我要写书评

暂无评论

AdIM-MVSNet: Adaptive depth Interval Multi-View Stereo Network for 3d reconstruction 2022

ADIM-MVSNet: Adaptive Depth Interval Multi-View Stereo Netwo...

引用

5th International conference on Image and Graphics Processing, ICIGP 2022

作者： Cheng, Wei Bai, Zhengyao Li, Junjie Liu, Huijie Yang, Lifang School of Information Science and Engineering Yunnan University China

ISBN: (纸本)9781450395465

Estimating depth from multiple images to recover 3d object surfaces is an important and challenging computer vision task. In this paper, an effective multi-view stereo network is proposed with a multi-scale feature aggregation module and adaptive estimation of depth range assumptions, namely AdIM-MVSNet. Particularly, multi-scale feature aggregation (MFA) module is presented to extract and aggregate features at different scales of images, which substantially improves the extraction of weak texture regions compared to general 2d convolutional neural networks (CNNs). In addition, adaptive depth interval module (AdIM) is proposed to improve the previous fixed depth interval partitioning, which allows the network to reasonably partition the depth prediction range during the refinement stage. Experimental results show that the proposed method can effectively conduct the multi-view 3d reconstruction of complex scenes and achieve state-of-the-art (SOTA) reconstruction results on the dTU dataset. © 2022 ACM.

关键词： Textures

来源：评论

学校读者我要写书评

暂无评论

New face recognition technologies based on 3dMM

New face recognition technologies based on 3DMM

引用

International conference on Artificial Intelligence, virtual Reality, and visualization (AIVRV)

作者： Huang, Zixuan YuYao 2 Middle Sch Ningbo Peoples R China

ISBN: (数字)9781510651838

ISBN: (纸本)9781510651838;9781510651821

Face recognition system includes face detection, face positioning, and face identification. ith the advent of the information age, identity authentication has become more and more important, and face recognition has become the mainstream method of identity verification due to its non-invasiveness, easy availability, and high reliability. With the current rapid development of artificial intelligence, it is of practical significance to introduce deep learning methods into face recognition. My work uses the caffe framework to design an 18-layer network model. At the same time, 448,808 pictures of 1,583 objects in the YouTube Face data set were used as training set, and 111,403 pictures of 1583 objects were used as verification sets. After preprocessing. These images, we entered them into the network for training our model. The facerecognition accuracy of the final model reached 99.7%. Next, my work did a forward-looking work for 3d face verification: single-view 3d face reconstruction. At present, the lack of open source 3d face database can be said to be the biggest obstacle to 3d face verification if you want to use deep learning algorithms. In order to solve this problem, my work will focus on the reconstruction of 3d human faces. Traditional 3d face reconstruction methods are either unstable or over-regularized. So I tried to apply the deep learning method to the 3d face reconstruction. First of all, in order to solve the problem of lacking 3d model data, we improved the current Multi-view 3d face reconstruction methods, using the 3d Morphable Models (3dMM) to generate huge numbers of labeled examples. Next, design the network and train it, the network finally implemented the function of constructing a 3d model of the object from a 2d picture of itself.

关键词： Face recognition 3dMM 3d face construction deep learning

来源：评论

学校读者我要写书评

暂无评论

3d Images Super-Resolution using Convolutional Neural Networks

3D Images Super-Resolution using Convolutional Neural Networ...

引用

Advancement in Technology (ICONAT), International conference for

作者： Trapty Agarwal Sachin Gupta Manashree Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Management Sanskriti University Mathura Uttar Pradesh India Department of Forensic Science School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

3-d image super-resolution (3-d-SR), the use of convolutional neural networks (CNNs), is a technique that is being explored to decorate the decision of three-d pics. With the aid of leveraging the electricity of deep mastering and CNN architectures, 3-d-SR is able to produce 3-d pictures from low-resolution 3d pix. The goal of this method is to get a better understanding of the missing functions from a low-resolution 3-d photograph that allows you to recover the lost details. The three-d-SR version makes use of a deep mastering framework to examine a mapping among a low-decision 3d picture and a high-decision 3d reconstruction. This mapping is then used to reconstruct a better-decision 3-d image of the equal scene from the low-decision model. Via the usage of this method, a clean development in resolution may be executed, which can then be used to permit further three-d image analysis.

关键词： visualization Solid modeling Three-dimensional displays Image analysis Electricity Superresolution Convolutional neural networks Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

LIVE-GS: LLM Powers Interactive VR by Enhancing Gaussian Splatting

LIVE-GS: LLM Powers Interactive VR by Enhancing Gaussian Spl...

引用

virtual Reality and 3d User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Haotian Mao Zhuoxiong Xu Siyue Wei Yule Quan Nianchen deng Xubo Yang Shanghai Jiao Tong University Shanghai AI Lab

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

We propose LIVE-GS, a highly realistic interactive Gaussian splatting system in VR environments powered by LLM. Our pipeline supports reconstructions and physically-based interactions in VR, integrating object-aware reconstruction, GPT-assisted inpainting, and a computationally efficient simulation framework. To enhance scene understanding, we prompt GPT-4o to analyze the physical properties of objects in the scene, thereby guiding physical simulations to align with real-world phenomena. Our experimental results demonstrate that with the assistance of LLM’s understanding and scene enhancement, our VR system can support complex and realistic interactions without requiring additional manual design or annotation.

关键词： Three-dimensional displays Annotations conferences Pipelines virtual reality User interfaces Visual effects Real-time systems Computational efficiency Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Neural reconstruction of Relightable Human Model from Monocular Video

Neural Reconstruction of Relightable Human Model from Monocu...

引用

IEEE/CVF International conference on Computer Vision (ICCV)

作者： Sun, Wenzhang Che, Yunlong Huang, Han Guo, Yandong Beijing Inst Technol Beijing Peoples R China AI2 Robot Beijing Peoples R China

ISBN: (纸本)9798350307184

Creating relightable and animatable human characters from monocular video at a low cost is a critical task for digital human modeling and virtual reality applications. This task is complex due to intricate articulation motion, a wide range of ambient lighting conditions, and pose-dependent clothing deformations. In this paper, we introduce a novel self-supervised framework that takes a monocular video of a moving human as input and generates a 3d neural representation capable of being rendered with novel poses under arbitrary lighting conditions. Our framework decomposes dynamic humans under varying illumination into neural fields in canonical space, taking into account geometry and spatially varying BRdF material properties. Additionally, we introduce pose-driven deformation fields, enabling bidirectional mapping between canonical space and observation. Leveraging the proposed appearance decomposition and deformation fields, our framework learns in a self-supervised manner. Ultimately, based on pose-driven deformation, recovered appearance, and physically-based rendering, the reconstructed human figure becomes relightable and can be explicitly driven by novel poses. We demonstrate significant performance improvements over previous works and provide compelling examples of relighting from monocular videos of moving humans in challenging, uncontrolled capture scenarios.

关键词：

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155页 << < 23 24 25 26 27 28 29 30 31 32 > >>

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：