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

10,952 篇 会议
774 册 图书
293 篇 期刊文献
4 件 标准

馆藏范围

12,023 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,000 篇 工学
- 4,591 篇 计算机科学与技术...
- 3,922 篇 软件工程
- 1,063 篇 光学工程
- 772 篇 电气工程
- 760 篇 生物医学工程（可授...
- 546 篇 信息与通信工程
- 501 篇 电子科学与技术（可...
- 486 篇 机械工程
- 434 篇 控制科学与工程
- 426 篇 生物工程
- 266 篇 土木工程
- 259 篇 建筑学
- 211 篇 仪器科学与技术
- 158 篇 化学工程与技术
- 140 篇 力学（可授工学、理...
- 137 篇 测绘科学与技术
- 102 篇 材料科学与工程（可...
2,501 篇 理学
- 1,377 篇 物理学
- 1,134 篇 数学
- 452 篇 生物学
- 215 篇 统计学（可授理学、...
- 180 篇 化学
- 101 篇 系统科学
994 篇 医学
- 879 篇 临床医学
- 320 篇 基础医学(可授医学...
- 260 篇 药学(可授医学、理...
811 篇 管理学
- 431 篇 管理科学与工程(可...
- 417 篇 图书情报与档案管...
- 158 篇 工商管理
105 篇 教育学
- 101 篇 教育学
89 篇 法学
89 篇 农学
37 篇 经济学
28 篇 文学
24 篇 艺术学
16 篇 军事学
1 篇 哲学

主题

3,333 篇 visualization
1,596 篇 rendering (compu...
1,251 篇 computer graphic...
1,115 篇 data visualizati...
689 篇 biomedical imagi...
682 篇 three-dimensiona...
524 篇 image segmentati...
489 篇 cameras
484 篇 computational mo...
481 篇 computer imaging...
420 篇 magnetic resonan...
381 篇 artificial intel...
377 篇 solid modeling
333 篇 three dimensiona...
333 篇 graphics
319 篇 computer science
309 篇 feature extracti...
308 篇 computer vision
306 篇 shape
298 篇 application soft...

机构

31 篇 school of comput...
25 篇 univ utah sci co...
24 篇 tsinghua univers...
23 篇 shanghai jiao to...
22 篇 institute for co...
17 篇 department of co...
16 篇 indian statistic...
15 篇 department of ma...
14 篇 department of co...
14 篇 faculty of infor...
14 篇 nanyang technolo...
14 篇 fraunhofer insti...
14 篇 peking universit...
13 篇 eindhoven univer...
13 篇 agh university o...
13 篇 zhejiang univ st...
12 篇 school of comput...
12 篇 imaging and visu...
12 篇 university of ca...
12 篇 department of co...

作者

20 篇 nassir navab
18 篇 osvaldo gervasi
18 篇 horst bischof
15 篇 huang mao lin
14 篇 ryszard tadeusie...
14 篇 scheuermann geri...
14 篇 linsen lars
13 篇 g.j. clapworthy
13 篇 mateu sbert
13 篇 marcin korytkows...
13 篇 jacek m. zurada
13 篇 m. sarfraz
12 篇 ertl thomas
12 篇 leonidas deligia...
12 篇 lotfi a. zadeh
12 篇 george bebis
12 篇 zhang jian j.
11 篇 bahram parvin
11 篇 darko koracin
11 篇 alexei sourin

语言

11,850 篇 英文
90 篇 俄文
59 篇 其他
27 篇 中文
1 篇 西班牙文
1 篇 法文

检索条件"任意字段=International Conference on Computer Graphics, Imaging and Visualization"

共 12023 条记录，以下是151-160 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 Healthcare with GPGPU and Energy Efficient NoC Architectures: A Comprehensive Survey

Advancing Healthcare with GPGPU and Energy Efficient NoC Arc...

引用

Ambient Intelligence in Health Care (ICAIHC), international conference on

作者： Panthagani Vijaya Babu Sonal Yadav Vijay Holimath Dept. of Computer Science & Engineering ViBram Silicon Hub National Institute of Technology Raipur India VividSparks IT Solutions Bangalore India

ISBN: (数字)9798331530259

ISBN: (纸本)9798331530266

General-purpose graphics Processing Units (GPGPU) have emerged as a transformative technology in healthcare and medical fields, harnessing their powerful parallel processing capabilities to handle complex computational challenges. Initially developed for graphics rendering, GPUs are now employed in high-performance tasks such as medical imaging, genomic analysis, drug discovery, and real-time patient monitoring, where vast data volumes and intensive computations are prevalent. GPGPU technology enhances processing efficiency, reduces latency, and supports faster, more accurate diagnostics and treatment planning. Complementing this advancement, Networks-On-Chip (NoC) designs, introduced in the early 2000s, have become a standard communication backbone for high-end CPUs and Systems-on-Chip (SoCs). Their low communication latency, high throughput, and energy efficiency make NoCs ideal for addressing the growing demands of GPU-based systems. However, achieving these performance objectives requires minimizing power dissipation, energy consumption, and costs. This research provides a comprehensive survey of NoC design models for multi-GPU systems, focusing on their role in energy-efficient and scalable architectures. It also highlights the impact of GPGPU in revolutionizing healthcare by meeting modern medical applications' computational and efficiency requirements.

关键词： Surveys Scalability Memory management graphics processing units Medical services Throughput Energy efficiency Real-time systems Computational efficiency Standards

来源：评论

学校读者我要写书评

暂无评论

Hybrid Deep Learning Architecture for Accurate Brain Tumor Classification

Hybrid Deep Learning Architecture for Accurate Brain Tumor C...

引用

Visual Analytics and Data visualization (ICVADV), international conference on

作者： R Bhuvaneswari Madhan B Mohamed Basman M Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

An important part of medical imaging is classifying brain tumors since precise detection is critical to an early diagnosis and for the planning of effective treatment. This study presents a hybrid deep learning model combining two well-established architectures, VGG16 and InceptionV3, to classify MRI images of brain between two classes: tumor and no tumor. This model combines the good of two complex convolutional neural networks (CNNs), taking the benefit of extracting features with VGG16 and spatial optimization with InceptionV3. The dataset of labeled brain MRI images is then used to train the hybrid model using transfer learning, fine tuning, regularization, and data augmentation is applied to the images to standardize their dimensions and normalize pixel values, as well as to increase the dataset size and decrease the risk of overfitting. Metrics such as precision, recall, F1-score, overall accuracy are applied to evaluate its classification accuracy. The output highlights the model effectiveness to discriminate between tumor and non-tumor classes and demonstrates its potential for automated brain tumor detection. The intention behind this work is to help radiologists to speed up and improve diagnostic accuracy to optimize patient prognoses in the overall management of tumors in brain.

关键词： Deep learning Accuracy Magnetic resonance imaging Visual analytics Transfer learning Brain tumors Brain modeling Feature extraction Data models Tuning

来源：评论

学校读者我要写书评

暂无评论

Assisting MoCap-Based Teleoperation of Robot Arm Using Augmented Reality Visualisations 25

Assisting MoCap-Based Teleoperation of Robot Arm Using Augme...

引用

ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Qiushi Zhou Antony Chacon Jiahe Pan Wafa Johal Aarhus University The University of Melbourne ETH Zurich

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Teleoperating a robot arm involves the human operator positioning the robot's end-effector or programming each joint. Whereas humans can control their own arms easily by integrating visual and proprioceptive feedback, it is challenging to control an external robot arm in the same way, due to its inconsistent orientation and appearance. We explore teleoperating a robot arm through motion-capture (MoCap) of the human operator's arm with the assistance of augmented reality (AR) visualisations. We investigate how AR helps teleoperation by visualising a virtual reference of the human arm alongside the robot arm to help users understand the movement mapping. We found that the AR overlay of a humanoid arm on the robot in the same orientation helped users learn the control. We discuss findings and future work on MoCap-based robot teleoperation.

关键词： visualization Human-robot interaction Propioception Humanoid robots Arms Manipulators Rendering (computer graphics) End effectors Robots Augmented reality

来源：评论

学校读者我要写书评

暂无评论

13th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2018

13th International Joint Conference on Computer Vision, Imag...

引用

13th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2018

ISBN: (纸本)9783030267551

The proceedings contain 18 papers. The special focus in this conference is on computer Vision, imaging and computer graphics Theory and Applications. The topics include: Flash, storm, and mistral: Hardware-friendly and high quality tone mapping;a simple and exact algorithm to solve linear problems with 1-based regularizers;spatial and spectral calibration of a multispectral-augmented endoscopic prototype;random forests based image colorization;a survey on databases of facial macro-expression and micro-expression;real-time head pose estimation by tracking and detection of keypoints and facial landmarks;contact-less, optical heart rate determination in the field ambient assisted living;effective facial expression recognition through multimodal imaging for traumatic brain injured patient’s rehabilitation;3D articulated model retrieval using depth image input;haptic and touchless user input methods for simple 3D interaction tasks: Interaction performance and user experience for people with and without impairments;recommendations from a study of a multimodal positive computing system for public speaking;utilisation of linguistic and paralinguistic features for academic presentation summarisation;An ROI visual-analytical approach for exploring uncertainty in reservoir models;a descriptive attribute-based framework for annotations in data visualization;tabularVis: An interactive relationship visualization tool supported by optimization and search algorithms;visual computing methods for assessing the well-being of older people.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Recent Advancements in Multi-Modal Medical Image Fusion Techniques using SWT, NSST, NSCT, and CNN

A Recent Advancements in Multi-Modal Medical Image Fusion Te...

引用

Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), international conference on

作者： Shailesh Bhosekar Prabhishek Singh Deepak Garg School of Computer Science and Artificial Intelligence SR University Warangal Telangana India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Image fusion is a method used in image processing to provide a more complete representation by amalgamating features and data from many images. Multimodal medical image fusion involves the integration of medical images from many imaging modalities, including computed tomography (CT) scans, positron emission tomography (PET), and magnetic resonance imaging (MRI), into one single dataset. This integration enhances the visualisation of anatomical structures and clinical situations, hence improving diagnostic accuracy by leveraging the strengths of each medium. This study employs MRI, CT, and PET scans as experimental modalities. This review aims to compare various multi modal medical image approach based on Stationary Wavelet Transform (SWT), Non-Subsampled Shearlet Transform (NSST), Convolutional Neural Network (CNN) and NonSubsampled Contourlet Transform (NSCT). This study examines the latest conventional and non-conventional research conducted within these disciplines. It further evaluates these approaches according to diverse image quality metrics and many quantitative assessments. According to this comparison, CNN-based fusion demonstrates superior results, as the overall visual and parametric quality of the fusion outcomes surpasses that of the other approaches evaluated.

关键词： Image quality Wavelet transforms visualization Reviews Magnetic resonance imaging Computed tomography Convolutional neural networks Positron emission tomography Medical diagnostic imaging Image fusion

来源：评论

学校读者我要写书评

暂无评论

Improving Image Super-Resolution Reconstruction with InceptionV3 and Dual Perceptual Loss

Improving Image Super-Resolution Reconstruction with Incepti...

引用

international ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Siriwan Chuengtheerapanit Warawut Kesornsukhon Kanabadee Srisomboon Luepol Pipanmekaporn San Ratanasanya Department of Computer and Information Science King Mongkut’s University of Norh Bangkok Bangkok Thailand Department of Electrical and Computer Engineering King Mongkut’s Universiy of North Bangkok Bangkok Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This paper proposes a method to improve the quality of image super-resolution (SR) by using the InceptionV3 network and Dual Perceptual Loss (DP Loss) within the Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) framework. Reconstruction of high-resolution images is enhanced by the proposed method in terms of both structural integrity and perceptual quality. The proposed method solves the limitations of previous models, including over-sharpening and color inaccuracies, which are prevalent in SR tasks. The proposed method, which replaces the ResNet Model with InceptionV3, outperforms the baseline ESRGAN-DP in Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Learned Perceptual Image Patch Similarity (LPIPS). It achieves up to 0.61% improvement in PSNR, 0.90% in SSIM, and 5.9% in LPIPS across multiple benchmark datasets.

关键词： visualization PSNR Image color analysis Superresolution Benchmark testing Feature extraction Solids Image reconstruction Standards Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

Explainable AI for Breast Cancer Diagnosis: A Convolutional Autoencoder with Modified Loss Functions and Grad-CAM visualization for Histopathology Image Classification

Explainable AI for Breast Cancer Diagnosis: A Convolutional ...

引用

Artificial Intelligence, Applications, Innovation and Ethics (AI2E), international conference for

作者： Hamza Zidoum ArunaDevi Karuppasamy Mazin Abdullatif Abdulrahman Mukhtar Maiya Al-Bahri Department of Computer Science Sultan Qaboos University Muscat Sultanate of Oman Department of Computing Sciences Gulf College Muscat Sultanate of Oman Sultan Qaboos University Muscat Sultanate of Oman Department of Pathology College of Medicine and Health Sciences Sultan Qaboos University Muscat Sultanate of Oman

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

The study proposes a novel deep learning model, a Convolutional Autoencoder with modified loss functions (CAE-MLS) for explainable breast cancer diagnosis through histopathology image analysis. To enhance model interpretability, we used Gradient-weighted Class Activation Mapping (GradCAM) visualization, which emphasizes areas of interest that affect the model's diagnostic decisions. The optimization of the model is achieved by using a custom loss function which combines mean absolute error, mean squared error, and structural similarity index to balance pixel-level accuracy with quality in image reconstruction. Our model achieves 91\% classification accuracy, with 93% precision for Malignant tumour detection. The proposed model attained a best-balanced performance for both classes, with F1-scores of 0.88 and 0.92 for benign and malignant cases in the 10x magnifications, respectively. Grad-CAM visualizations confirm the model's ability to focus on clinically relevant image regions at both 10x and 40x magnifications, providing healthcare professionals with transparent insights into the decision-making process.

关键词： visualization Accuracy Histopathology Autoencoders computer architecture Breast cancer Optimization Medical diagnostic imaging Image reconstruction Image classification

来源：评论

学校读者我要写书评

暂无评论

Advanced Motion Recognition Using High-Resolution Infrared imaging and Enhanced Image Processing Techniques

Advanced Motion Recognition Using High-Resolution Infrared I...

引用

Disruptive Technologies (ICDT), international conference on

作者： Prafull Mishra Rishabh Srivastava Prerna Singh Vineet Shrivastava Devesh Garg Department of Computer Science & Engineering Raj Kumar Goel Institute of Technology Ghaziabad UP India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Over the past few years, infrared (IR) motion detection has become more important in domains such as security, wildlife monitoring, and nighttime surveillance, when standard vision-based systems frequently fail. The approach of infrared video detection using convolutional neural networks is been implemented in this research work. Infrared imaging is particularly useful for collecting temperature-based data in low-visibility or dark conditions, enabling for the monitoring of activities that would otherwise be difficult to trace. The suggested approach preprocesses grayscale infrared pictures, normalizing them and scaling to fit the input requirements of a custom-built CNN. Through a sequence of convolutional and pooling layers, the CNN collects characteristics related to motion patterns in IR pictures, learning to discriminate between frames having motion and those that do not. The proposed system was developed with the help of pre-trained data values of infrared pictures, and performance was tested using multiple parameters that includes various visualization figures such as accuracy-precision graph, recall, and ROC-AUC, to show its usefulness. This real-time approach combines a CNN with a video processing pipeline to identify motion in an infrared movie. It uses visualizations like as confusion matrices, accuracy-loss curves, and precision-recall curves to give insights into model design, implementation details, and experimental results. The results reveal that CNNs can accurately discern motion in infrared pictures, paving the way for automated low-light surveillance.

关键词： Surveillance Wildlife Data visualization Infrared imaging Streaming media Real-time systems Motion detection Convolutional neural networks Image preprocessing Standards

来源：评论

学校读者我要写书评

暂无评论

Exploring Explainable AI in Brain Tumor Detection: A Hybrid Approach Using EfficientNet and CBAM

Exploring Explainable AI in Brain Tumor Detection: A Hybrid ...

引用

Device Intelligence, Computing and Communication Technologies, (DICCT), international conference on

作者： Aqib Nazir Mir Danish Raza Rizvi Department of Computer Engineering Jamia Millia Islamia Delhi India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

This research presents an advanced methodology for brain tumour classification using magnetic resonance imaging (MRI), combining the EfficientNet-B0 architecture with Convolutional Block Attention Modules (CBAM). The proposed model effectively captures both channel and spatial attention by replacing the Squeeze-and-Excitation (SE) modules with CBAM, enhancing feature extraction and classification accuracy. The framework is evaluated on a comprehensive dataset comprising four classes: pituitary no tumour, meningioma, and glioma. Leveraging transfer learning and Grad-CAM-based explainability, the proposed model attains an outstanding accuracy of 99%, with weighted F1 score and macro scores exceeding 98%. Comparative analyses confirm its superior performance against state-of-the-art methods, particularly in classifying complex tumour types. The combination of accuracy, efficiency, and interpretability highlights the potential of this approach for real-world medical diagnostics.

关键词： visualization Accuracy Attention mechanisms Magnetic resonance imaging Transfer learning Feature extraction Brain modeling Real-time systems Reliability Tumors

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the 10th IASTED international conference on computer graphics and imaging, CGIM 2008

Proceedings of the 10th IASTED International Conference on C...

引用

10th IASTED international conference on computer graphics and imaging, CGIM 2008

ISBN: (纸本)9780889867192

The proceedings contain 50 papers. The topics discussed include: fast full search algorithm using adaptive search order;mesh cutting for aided 3D digital model setup and planning;an introduced blocked-wavelet algorithm for signal and time improvements of images with multiple regions;interactive circuit diagram visualization;a proposal modification of the 3OT chain code;accuracy of GPU-based B-spline evaluation;the simulation of cloth using accurate physical parameters;comparison of two real-time image processing system approaches;camera control for remote transcription system;a solution to the next best view problem based on D-spheres for 3D object recognition;fast multiple reference frame selection algorithm in H.264/AVC;and video super-resolution by integrating SAD and NCC matching criterion for multiple moving objects.

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500页 << < 12 13 14 15 16 17 18 19 20 21 > >>

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：