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

283 篇 会议
41 册 图书
3 篇 期刊文献

馆藏范围

327 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

171 篇 工学
- 152 篇 计算机科学与技术...
- 93 篇 软件工程
- 47 篇 光学工程
- 35 篇 信息与通信工程
- 28 篇 生物工程
- 22 篇 电气工程
- 16 篇 控制科学与工程
- 9 篇 电子科学与技术（可...
- 8 篇 化学工程与技术
- 8 篇 生物医学工程（可授...
- 6 篇 网络空间安全
- 5 篇 机械工程
- 5 篇 安全科学与工程
- 3 篇 仪器科学与技术
- 3 篇 材料科学与工程（可...
- 3 篇 建筑学
- 3 篇 农业工程
78 篇 理学
- 48 篇 物理学
- 30 篇 生物学
- 25 篇 数学
- 11 篇 统计学（可授理学、...
- 8 篇 化学
21 篇 医学
- 16 篇 临床医学
- 4 篇 公共卫生与预防医...
- 3 篇 基础医学(可授医学...
- 3 篇 特种医学
18 篇 管理学
- 10 篇 管理科学与工程(可...
- 9 篇 图书情报与档案管...
- 5 篇 工商管理
4 篇 农学
- 4 篇 作物学
2 篇 法学
2 篇 教育学

主题

37 篇 computer vision
25 篇 image processing...
21 篇 artificial intel...
20 篇 pattern recognit...
20 篇 computer imaging...
17 篇 machine learning
14 篇 computer applica...
13 篇 computer systems...
12 篇 signal, image an...
11 篇 deep learning
8 篇 image processing
6 篇 computers and ed...
5 篇 vision transform...
5 篇 low-level vision
4 篇 image enhancemen...
4 篇 object detection
4 篇 cell microscopy
4 篇 image segmentati...
4 篇 graphics process...
4 篇 stereo image pro...

机构

17 篇 microsoft resear...
17 篇 microsoft res as...
12 篇 tsinghua univers...
7 篇 university of sc...
7 篇 univ sci & techn...
6 篇 national key lab...
6 篇 shanghai collabo...
6 篇 shanghai key lab...
5 篇 university of te...
5 篇 dalian universit...
5 篇 university of sy...
5 篇 institute of aut...
5 篇 shenzhen univers...
4 篇 key laboratory o...
4 篇 national enginee...
4 篇 university of ud...
4 篇 tsinghua univ pe...
4 篇 microsoft cloud ...
4 篇 university of yo...
4 篇 vision and image...

作者

8 篇 han hu
7 篇 hu han
6 篇 zuxuan wu
6 篇 min xu
5 篇 hui huang
5 篇 jing dong
5 篇 yu-gang jiang
5 篇 jiwen lu
5 篇 risheng liu
5 篇 wanli ouyang
5 篇 huchuan lu
4 篇 gian luca forest...
4 篇 qi dai
4 篇 zhiguo cao
4 篇 dongdong chen
4 篇 edwin hancock
4 篇 boxin shi
4 篇 jean-jacques rou...
4 篇 zheng zhang
4 篇 andrea fusiello

语言

322 篇 英文
5 篇 其他
3 篇 中文

检索条件"任意字段=2023 Asia Conference on Computer Vision, Image Processing and Pattern Recognition, CVIPPR 2023"

共 327 条记录，以下是71-80 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：

Lightweight Real-Time image Super-Resolution Network for 4K images

Lightweight Real-Time Image Super-Resolution Network for 4K ...

引用

2023 IEEE/CVF conference on computer vision and pattern recognition Workshops, CVPRW 2023

作者： Gankhuyag, Ganzorig Yoon, Kihwan Park, Jinman Son, Haeng Seon Min, Kyoungwon Korea Electronics Technology Institute Korea Republic of

ISBN: (纸本)9798350302493

Single-image super-resolution technology has become a topic of extensive research in various applications, aiming to enhance the quality and resolution of degraded images obtained from low-resolution sensors. However, most existing studies on single-image super-resolution have primarily focused on developing deep learning networks operating on high-performance graphics processing units. Therefore, this study proposes a lightweight real-time image super-resolution network for 4K images. Furthermore, we applied a reparameterization method to improve the network performance without incurring additional computational costs. The experimental results demonstrate that the proposed network achieves a PSNR of 30.15 dB and an inference time of 4.75 ms on an RTX 3090Ti device, as evaluated on the NTIRE 2023 Real-Time Super-Resolution validation scale X3 dataset. The code is available at https://***/Ganzooo/***. © 2023 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

processing 3D Point Clouds for High-Throughput Plant Phenotyping 8th

Processing 3D Point Clouds for High-Throughput Plant Phenoty...

引用

8th National conference on computer vision, pattern recognition, image processing and Graphics-NCVPRIPG

作者： Dagar, Preety Arora, Alka Kumar, Sudhir Marwaha, Sudeep Jain, Rajni Chaurasia, Himanshushekhar Chinnusamy, Vishwanathan ICAR IASRI Div Comp Applicat Library Ave New Delhi 110012 India IARI Pusa ICAR IARI Div Plant Physiol New Delhi 110012 India ICAR CIRCOT Mumbai 400019 Maharashtra India

ISBN: (纸本)9789819752119;9789819752126

In recent years, measuring three-dimensional (3D) surface information has gained a great interest in plant phenotyping because it can represent the nature of plant architecture better than conventional 2D images. This paper presents an approach for processing 3D point clouds converted from 2D RGB images in the context of high-throughput plant phenotyping. High-resolution RGB multi-view imagery of a Chickpea plant was collected using a high-end camera. Based on these image sequences, 3D point cloud reconstruction of the canopy was conducted and analyzed. Later sophisticated 3D operations were performed on these images including 3D downsampling and after that clustering was performed on the processed point cloud. The information generated can help in the evaluation of crop traits and provide accurate statistics for the assessment of their growth parameters.

关键词： 3D image processing 2D to 3D image conversion Open3D 3D image processing for plant phenotyping

来源：评论

学校读者我要写书评

暂无评论

Improving Person Re-identification Through Low-Light image Enhancement 12th

Improving Person Re-identification Through Low-Light Image E...

引用

12th International conference on pattern recognition Applications and Methods (ICPRAM)

作者： Santana, Oliverio J. Lorenzo-Navarro, Javier Freire-Obregon, David Hernandez-Sosa, Daniel Castrillon-Santana, Modesto Univ Las Palmas Gran Canaria SIANI Las Palmas Gran Canaria Spain

ISBN: (纸本)9783031547256;9783031547263

Person re-identification (ReID) is a popular area of research in the field of computer vision. Despite the significant advancements achieved in recent years, most of the current methods rely on datasets containing subjects captured with good lighting under static conditions. ReID presents a significant challenge in real-world sporting scenarios, such as long-distance races that take place over varying lighting conditions, ranging from bright daylight to night-time. Unfortunately, increasing the exposure time on the capture devices to mitigate low-light environments is not a feasible solution, as it would result in blurry images due to the motion of the runners. This paper surveys several low-light image enhancement methods and finds that including an image pre-processing step in the ReID pipeline before extracting the distinctive body features of the subjects can lead to significant improvements in performance.

关键词： computer vision Person re-identification Sporting event Ultra-trail running In the wild dataset Low-light image enhancement

来源：评论

学校读者我要写书评

暂无评论

Prototype of a System to Assist the Urologist in the recognition of Urinary Bladder Tumors in MRI images 10

Prototype of a System to Assist the Urologist in the Recogni...

引用

10th International conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Martinez, Ares Ulises Juarez Lomas, Jaime Hugo Puebla Talamantes, Jose Felix Serrano ESCOM IPN Dept Syst Engn Computat Mexico City DF Mexico CIDETEC IPN Virtual Real Lab Mexico City DF Mexico

ISBN: (纸本)9798350359374

The proposal aims to develop a prototype system to detect possible bladder tumors. The system Will use image processing techniques, computer vision, segmentation, pattern recognition and machine learning. The prototype Will load images of the urinary bladder (hollow, distensible muscular organ) and obtain a classification of possible bladder tumors.

关键词： urinary bladder image processing artificial intelligence segmentation and machine learning

来源：评论

学校读者我要写书评

暂无评论

Machine vision Applied to Backscattered Electron Imaging 6

Machine Vision Applied to Backscattered Electron Imaging

引用

6th IEEE International conference on pattern recognition and Artificial Intelligence, PRAI 2023

作者： Huang, Junyuan Zhang, Wei Chen, Jingyun Beihang University School of Mechanical Engineering and Automation Beijing China Beijing Institute of Space Launch Technology Beijing China

ISBN: (纸本)9798350325485

Electron beam processing usually needs to be carried out in a vacuum environment. The influence of high temperature and high concentration of metal vapor makes it difficult for traditional machine vision observation systems to perform long-Term observation. In this paper, a machine vision algorithm was used, a quadrupole plate sensor and image fusion algorithm were adopted, and the combination of software and hardware was realized. Finally, we solved the problems of scale imbalance and slice model scanning order in the imaging process and successfully realized clear observation of the surface in all directions. The backscattered electron signal imaging technology has been successfully applied to the electron beam processing process, which meets the online observation requirements of the electron beam processing process. © 2023 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

RODIN: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion

RODIN: A Generative Model for Sculpting 3D Digital Avatars U...

引用

IEEE/CVF conference on computer vision and pattern recognition (CVPR)

作者： Wang, Tengfei Zhang, Bo Zhang, Ting Gu, Shuyang Bao, Jianmin Baltrusaitis, Tadas Shen, Jingjing Chen, Dong Wen, Fang Chen, Qifeng Guo, Baining HKUST Hong Kong Peoples R China Microsoft Res Beijing Peoples R China Intern Microsoft Res Hong Kong Peoples R China

ISBN: (纸本)9798350301298

This paper presents a 3D diffusion model that automatically generates 3D digital avatars represented as neural radiance fields (NeRFs). A significant challenge for 3D diffusion is that the memory and processing costs are prohibitive for producing high-quality results with rich details. To tackle this problem, we propose the roll-out diffusion network (RODIN), which takes a 3D NeRF model represented as multiple 2D feature maps and rolls out them onto a single 2D feature plane within which we perform 3D-aware diffusion. The RODIN model brings much-needed computational efficiency while preserving the integrity of 3D diffusion by using 3D-aware convolution that attends to projected features in the 2D plane according to their original relationships in 3D. We also use latent conditioning to orchestrate the feature generation with global coherence, leading to high-fidelity avatars and enabling semantic editing based on text prompts. Finally, we use hierarchical synthesis to further enhance details. The 3D avatars generated by our model compare favorably with those produced by existing techniques. We can generate highly detailed avatars with realistic hairstyles and facial hair. We also demonstrate 3D avatar generation from image or text, as well as text-guided editability.

关键词： vision + graphics

来源：评论

学校读者我要写书评

暂无评论

Research on intelligent insect species identification based on computer vision 7

Research on intelligent insect species identification based ...

引用

7th International conference on Mechatronics and Intelligent Robotics, ICMIR 2023

作者： Huang, Bin Nanchang Institute of Technology Jiangxi Nanchang330044 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

image-based insect species identification is a comprehensive application of computer vision technology, image processing technology and pattern recognition technology to realize insect species identification. It is of great significance to find and identify crop insects in time and quickly, so as to take corresponding measures to prevent and control pests in time and reduce the losses caused by pests. In this paper, intelligent insect species identification based on computer vision is studied. For insect images, using feature fusion technology will obtain more comprehensive insect image features, which will greatly improve the recognition accuracy and improve the recognition efficiency of the system. In the learning process, firstly, a certain number of insect images are selected as training samples, and the feature vectors of insects are extracted as the input vectors of SVM(support vector machine) training, and the input vectors are learned to get the best classification model. The experimental results show that the average recognition rate of insects by feature fusion is 94.747%. The experimental results show that the research results of this paper provide theoretical and practical basis for intelligent insect species recognition technology based on computer vision. © 2023 SPIE. All rights reserved.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Learning Key Features Transformer Network for Point Cloud processing 6th

Learning Key Features Transformer Network for Point Cloud Pr...

引用

6th Chinese conference on pattern recognition and computer vision (PRCV)

作者： You, Guobang Hu, Yikun Liu, Yimei Liu, Haoyan Fan, Hao Ocean Univ China Coll Comp Sci & Technol Qingdao Peoples R China

ISBN: (纸本)9789819984312;9789819984329

Due to the unordered and irregular nature of point cloud data, it is challenging for neural networks to learn from it. Attention mechanisms have shown promising results in point cloud processing. It is also inherently permutation-invariant when dealing with a set of points, which makes it ideal for point cloud learning. In this paper, an attention-based encoder-decoder architecture called KFT-Net (Key Features Transformer) is designed for point cloud classification and segmentation tasks. KFT-Net has improved upon previous methods by capturing long-range contextual information, preserving important attention scores, and utilizing convolutional neural networks to extract local features. Additionally, to enhance the computational efficiency, we introduce the Top-k operation into the attention mechanism and utilize the average pooling operation to improve attention score calculation and feature extraction efficiency. Extensive experiments validate the effectiveness of the KFT-Net, demonstrating impressive performance in point cloud classification and segmentation tasks.

关键词： Point cloud Self-attention Feature extraction Classification Segmentation

来源：评论

学校读者我要写书评

暂无评论

Sparse Multimodal vision Transformer for Weakly Supervised Semantic Segmentation

Sparse Multimodal Vision Transformer for Weakly Supervised S...

引用

2023 IEEE/CVF conference on computer vision and pattern recognition Workshops, CVPRW 2023

作者： Hanna, Joëlle Mommert, Michael Borth, Damian University of St.Gallen AIML Lab School of Computer Science Switzerland

ISBN: (纸本)9798350302493

vision Transformers have proven their versatility and utility for complex computer vision tasks, such as land cover segmentation in remote sensing applications. While performing on par or even outperforming other methods like Convolutional Neural Networks (CNNs), Transformers tend to require even larger datasets with fine-grained annotations (e.g., pixel-level labels for land cover segmentation). To overcome this limitation, we propose a weakly-supervised vision Transformer that leverages image-level labels to learn a semantic segmentation task to reduce the human annotation load. We achieve this by slightly modifying the architecture of the vision Transformer through the use of gating units in each attention head to enforce sparsity during training and thereby retaining only the most meaningful heads. This allows us to directly infer pixel-level labels from image-level labels by post-processing the un-pruned attention heads of the model and refining our predictions by iteratively training a segmentation model with high fidelity. Training and evaluation on the DFC2020 dataset show that our method1 not only generates high-quality segmentation masks using image-level labels, but also performs on par with fully-supervised training relying on pixel-level labels. Finally, our results show that our method is able to perform weakly-supervised semantic segmentation even on small-scale datasets. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

3D Human Pose Estimation in Video with Temporal and Spatial Transformer

3D Human Pose Estimation in Video with Temporal and Spatial ...

引用

2023 International conference on image, Signal processing, and pattern recognition, ISPP 2023

作者： Peng, Sha Hu, Jiwei School of Information Engineering Wuhan University of Technology Wuhan China

ISBN: (纸本)9781510666351

Previous works on 3D human pose estimation have concentrated on predicting the 3D pose of the human body from a single image, ignoring correlation between adjacent frames in video. We design a transformer network structure that can extract video temporal information, and enhance the accuracy of human pose prediction by encoding relative position with temporal fusion transformer structure to enhance local feature learning capability. On Human3.6M, we quantitatively and qualitatively analyze our method. Research suggests that our TSFormer achieves state-of-the-art performance. © 2023 SPIE.

关键词： computer vision

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33页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：