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

4,653 篇 会议
2 篇 期刊文献

馆藏范围

4,655 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,715 篇 工学
- 1,623 篇 计算机科学与技术...
- 182 篇 软件工程
- 142 篇 机械工程
- 133 篇 光学工程
- 41 篇 生物工程
- 29 篇 信息与通信工程
- 18 篇 电气工程
- 9 篇 电子科学与技术（可...
- 9 篇 化学工程与技术
- 9 篇 交通运输工程
- 8 篇 控制科学与工程
- 8 篇 生物医学工程（可授...
- 7 篇 安全科学与工程
- 4 篇 材料科学与工程（可...
- 4 篇 建筑学
- 3 篇 土木工程
- 3 篇 农业工程
173 篇 理学
- 135 篇 物理学
- 42 篇 生物学
- 30 篇 数学
- 16 篇 统计学（可授理学、...
- 10 篇 化学
- 2 篇 大气科学
14 篇 管理学
- 7 篇 管理科学与工程(可...
- 7 篇 图书情报与档案管...
- 3 篇 工商管理
10 篇 医学
- 10 篇 临床医学
5 篇 法学
- 3 篇 社会学
- 2 篇 法学
3 篇 教育学
- 3 篇 教育学
2 篇 农学
1 篇 经济学

主题

2,867 篇 computer vision
1,227 篇 training
1,038 篇 pattern recognit...
870 篇 computational mo...
794 篇 conferences
693 篇 visualization
593 篇 three-dimensiona...
469 篇 codes
460 篇 benchmark testin...
422 篇 semantics
420 篇 computer archite...
349 篇 accuracy
301 篇 adaptation model...
282 篇 feature extracti...
267 篇 transformers
242 篇 cameras
225 篇 diffusion models
223 篇 solid modeling
214 篇 pipelines
210 篇 measurement

机构

72 篇 tsinghua univers...
69 篇 zhejiang univers...
58 篇 university of sc...
57 篇 shanghai jiao to...
52 篇 google research
47 篇 nanyang technolo...
44 篇 national univers...
40 篇 shanghai ai labo...
39 篇 university of ch...
37 篇 adobe research
37 篇 the university o...
37 篇 the chinese univ...
35 篇 stanford univers...
34 篇 harbin institute...
34 篇 shanghai artific...
34 篇 carnegie mellon ...
33 篇 university of el...
30 篇 peng cheng labor...
30 篇 sun yat-sen univ...
29 篇 s-lab nanyang te...

作者

75 篇 timofte radu
24 篇 yu qiao
22 篇 luc van gool
19 篇 ying shan
16 篇 van gool luc
15 篇 radu timofte
14 篇 xin li
13 篇 li xin
12 篇 chen chen
12 篇 zhang zhao
12 篇 boxin shi
11 篇 lizhuang ma
11 篇 fan haoqiang
11 篇 loy chen change
11 篇 zheng-jun zha
11 篇 liu shuaicheng
11 篇 kai zhang
11 篇 marcos v. conde
11 篇 chen wei-ting
11 篇 ziwei liu

语言

4,654 篇 英文
1 篇 中文

检索条件"任意字段=2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024"

共 4655 条记录，以下是1291-1300 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：

MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture

MTLSegFormer: Multi-task Learning with Transformers for Sema...

引用

2023 ieee/cvf conference on computer vision and pattern recognition workshops, cvprw 2023

作者： Goncalves, Diogo Nunes Marcato, Jose Zamboni, Pedro Pistori, Hemerson Li, Jonathan Nogueira, Keiller Goncalves, Wesley Nunes Federal University of Mato Grosso Do Sul Faculty of Computer Science Av. Costa e Silva Campo Grande79070-900 MS Brazil Federal University of Mato Grosso Do Sul Faculty of Engineering Architecture and Urbanism and Geography Av. Costa e Silva Campo Grande79070-900 MS Brazil Dom Bosco Catholic University INOVISAO Avenida Tamandaré 6000 Campo Grande79117-900 MS Brazil University of Waterloo Department of Geography and Environmental Management WaterlooONN2L 3G1 Canada University of Stirling Scotland StirlingFK9 4LA United Kingdom

ISBN: (纸本)9798350302493

Multi-task learning has proven to be effective in improving the performance of correlated tasks. Most of the existing methods use a backbone to extract initial features with independent branches for each task, and the exchange of information between the branches usually occurs through the concatenation or sum of the feature maps of the branches. However, this type of information exchange does not directly consider the local characteristics of the image nor the level of importance or correlation between the tasks. In this paper, we propose a semantic segmentation method, MTLSegFormer, which combines multi-task learning and attention mechanisms. After the backbone feature extraction, two feature maps are learned for each task. The first map is proposed to learn features related to its task, while the second map is obtained by applying learned visual attention to locally re-weigh the feature maps of the other tasks. In this way, weights are assigned to local regions of the image of other tasks that have greater importance for the specific task. Finally, the two maps are combined and used to solve a task. We tested the performance in two challenging problems with correlated tasks and observed a significant improvement in accuracy, mainly in tasks with high dependence on the others. © 2023 ieee.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Towards Learning Image Similarity from General Triplet Labels

Towards Learning Image Similarity from General Triplet Label...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Radu Dondera Greenfield Vision

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Metric learning for images has so far focused overwhelmingly on a class-based definition of similarity: two images are similar if they belong to the same class and dissimilar otherwise. Impressive results were achieved on datasets for fine grained categorization, but performance is nearing saturation. Recent work in neuroscience and psychology produced datasets with other types of similarity labels, e.g. the outlier in a group of three, but traditional metric learning methods are ill-suited to such data because of low density of labels. To overcome this difficulty, we propose a novel approach in the teacher-student learning paradigm. Multiple teacher models learn to embed images based only on relations with other images, and then a student model learns to embed images based on both content and dense relations provided by the teachers. We show significant improvement over existing triplet based metric learning methods, both in result quality and in training efficiency. Additionally, through experiments on class based datasets, we show the generality of approaching metric learning via knowledge transfer. Code is available at ***/greenfieldvision/tdml.

关键词： Measurement Training Learning systems Visualization Neuroscience Psychology Focusing

来源：评论

学校读者我要写书评

暂无评论

Residual-based Language Models are Free Boosters for Biomedical Imaging Tasks

Residual-based Language Models are Free Boosters for Biomedi...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Zhixin Lai Jing Wu Suiyao Chen Yucheng Zhou Naira Hovakimyan Cornel University University of Illinois at Urbana-Champaign University of South Florida University of Macau

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

In this study, we uncover the unexpected efficacy of residual-based large language models (LLMs) as part of encoders for biomedical imaging tasks, a domain traditionally devoid of language or textual data. The approach diverges from established methodologies by utilizing a frozen transformer block, extracted from pre-trained LLMs, as an innovative encoder layer for the direct processing of visual tokens. This strategy represents a significant departure from the standard multi-modal vision-language frameworks, which typically hinge on language-driven prompts and inputs. We found that these LLMs could boost performance across a spectrum of biomedical imaging applications, including both 2D and 3D visual classification tasks, serving as plug-and-play boosters. More interestingly, as a byproduct, we found that the proposed framework achieved superior performance, setting new state-of-the-art results on extensive, standardized datasets in MedMNIST-2D and 3D. Through this work, we aim to open new avenues for employing LLMs in biomedical imaging and enriching the understanding of their potential in this specialized domain. The code is available at https://***/ZhixinLai/LLMBoostMedical

关键词： Visualization Three-dimensional displays Large language models conferences Fasteners Transformers pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Weakly Supervised End2End Deep Visual Odometry

Weakly Supervised End2End Deep Visual Odometry

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Amin Abouee Ashwanth Ravi Lars Hinneburg Mateusz Dziwulski Florian Ölsner Jürgen Hess Stefan Milz Patrick Mäder Spleenlab GmbH Germany Technical University Ilmenau Ilmenau Germany

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Visual odometry is an ill-posed problem and utilized in many robotics applications, especially automated driving for mapless navigation. Recent applications have shown that deep models outperform traditional approaches especially in localization accuracy and furthermore significantly reduce catastrophic failures. The disadvantage of most of these models is a strong dependence on high-quantity and high-quality ground truth data. However, accurate and dense depth ground truth data for real world datasets is difficult to obtain. As a result, deep models are often trained on synthetic data which introduces a domain gap. We present a weakly supervised approach to overcome this limitation. Our approach uses estimated optical flow for training that can be generated without the need for high-quality dense depth ground truth. Instead, it only requires ground truth poses and raw camera images for training. In the experiments, we show that our approach enables deep visual odometry to be efficiently trained on the target domain (real data) while achieving state-of-the-art performance on the KITTI dataset.

关键词： Training Accuracy Navigation Robot vision systems Cameras Data models pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Dissecting the High-Frequency Bias in Convolutional Neural Networks

Dissecting the High-Frequency Bias in Convolutional Neural N...

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Abello, Antonio A. Hirata Jr, Roberto Wang, Zhangyang Univ Sao Paulo Butanta Sao Paulo SP Brazil Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9781665448994

For convolutional neural networks (CNNs), a common hypothesis that explains both their generalization capability and their characteristic brittleness is that these models are implicitly regularized to rely on imperceptible high-frequency patterns, more than humans would do. This hypothesis has seen some empirical validation, but most works do not rigorously divide the image frequency spectrum. We present a model to divide the spectrum in disjointed discs based on the distribution of energy and apply simple feature importance procedures to test whether high-frequencies are more important than lower ones. We find evidence that mid or high-level frequencies are disproportionately important for CNNs. The evidence is robust across different datasets and networks. Moreover, we find the diverse effects of the network's attributes, such as architecture and depth, on frequency bias and robustness in general.

关键词： computer vision conferences computer architecture Frequency conversion Robustness Frequency diversity pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Two-Person Interaction Augmentation with Skeleton Priors

Two-Person Interaction Augmentation with Skeleton Priors

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Baiyi Li Edmond S. L. Ho Hubert P. H. Shum He Wang University of Leeds United Kingdom University of Glasgow United Kingdom Durham University United Kingdom University College London United Kingdom

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Close and continuous interaction with rich contacts is a crucial aspect of human activities (e.g. hugging, dancing) and of interest in many domains like activity recognition, motion prediction, character animation, etc. However, acquiring such skeletal motion is challenging. While direct motion capture is expensive and slow, motion editing/generation is also non-trivial, as complex contact patterns with topological and geometric constraints have to be retained. To this end, we propose a new deep learning method for two-body skeletal interaction motion augmentation, which can generate variations of contact-rich interactions with varying body sizes and proportions while retaining the key geometric/topological relations between two bodies. Our system can learn effectively from a relatively small amount of data and generalize to drastically different skeleton sizes. Through exhaustive evaluation and comparison, we show it can generate high-quality motions, has strong generalizability and outperforms traditional optimization-based methods and alternative deep learning solutions.

关键词： Deep learning computer vision conferences Activity recognition Animation Skeleton Motion capture

来源：评论

学校读者我要写书评

暂无评论

A Dual-Mode Approach for vision-Based Navigation in a Lunar Landing Scenario

A Dual-Mode Approach for Vision-Based Navigation in a Lunar ...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Luca Ostrogovich Roberto Del Prete Giuseppe Tomasicchio Nicolas Longépé Alfredo Renga Department of Industrial Engineering University of Naples Federico II Telespazio SRL Φ-Lab ESA ESRIN

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

In this research, a novel approach for autonomous spacecraft navigation, particularly in lunar contexts, is presented, focusing on vision-based techniques. The system incorporates lunar crater recognition in conjunction with feature tracking to enhance the accuracy of spacecraft navigation. This system underwent comprehensive evaluation through a purpose-built software simulation, replicating lunar conditions for thorough evaluation and refinement. The methodology integrates established navigational methods with advanced artificial intelligence algorithms, resulting in significant navigational accuracy. The system demonstrates precise capabilities in determining the spacecraft position, with an average accuracy of approximately 270 m for the absolute navigation mode, while the relative mode exhibited an average error of 27.4 m and 0.8 m in determining the horizontal and vertical lander displacements relative to terrain. Initial tests on embedded systems—akin to those on-board spacecraft—were conducted. These tests are pivotal in demonstrating the system’s operational viability within the constraints of limited bandwidth and rapid processing requirements characteristic of space missions. The promising results from these tests suggest potential applicability in real-world space missions, enhancing autonomous navigation capabilities in lunar and potentially other extraterrestrial environments.

关键词： Space vehicles Accuracy Navigation Space missions Moon Software algorithms Switches

来源：评论

学校读者我要写书评

暂无评论

DehazeDCT: Towards Effective Non-Homogeneous Dehazing via Deformable Convolutional Transformer

DehazeDCT: Towards Effective Non-Homogeneous Dehazing via De...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Wei Dong Han Zhou Ruiyi Wang Xiaohong Liu Guangtao Zhai Jun Chen McMaster University Shanghai Jiao Tong University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Image dehazing, a pivotal task in low-level vision, aims to restore the visibility and detail from hazy images. Many deep learning methods with powerful representation learning capability demonstrate advanced performance on non-homogeneous dehazing, however, these methods usually struggle with processing high-resolution images (e.g., 4000 × 6000) due to their heavy computational demands. To address these challenges, we introduce an innovative non-homogeneous Dehazing method via Deformable Convolutional Transformer-like architecture (DehazeDCT). Specifically, we first design a transformer-like network based on deformable convolution v4, which offers long-range dependency and adaptive spatial aggregation capabilities and demonstrates faster convergence and forward speed. Furthermore, we leverage a lightweight Retinex-inspired transformer to achieve color correction and structure refinement. Extensive experiment results and highly competitive performance of our method in NTIRE 2024 Dense and Non-Homogeneous Dehazing Challenge, ranking second among all 16 submissions, demonstrate the superior capability of our proposed method. The code is available: https://***/movingforward100/Dehazing_R.

关键词： Convolutional codes Representation learning Image color analysis Convolution computer architecture Transformer cores Transformers

来源：评论

学校读者我要写书评

暂无评论

PCQA: A Strong Baseline for AIGC Quality Assessment Based on Prompt Condition

PCQA: A Strong Baseline for AIGC Quality Assessment Based on...

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Xi Fang Weigang Wang Xiaoxin Lv Jun Yan DP Technology Cisco Shopee TongJi University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

The development of Large Language Models (LLM) and Diffusion Models brings the boom of Artificial Intelligence Generated Content (AIGC). It is essential to build an effective quality assessment framework to provide a quantifiable evaluation of different images or videos based on the AIGC technologies. The content generated by AIGC methods is driven by the crafted prompts. Therefore, it is intuitive that the prompts can also serve as the foundation of the AIGC quality assessment. This study proposes an effective AIGC quality assessment (QA) framework. First, we propose a hybrid prompt encoding method based on a dual-source CLIP (Contrastive Language-Image Pre-Training) text encoder to understand and respond to the prompt conditions. Second, we propose an ensemble-based feature mixer module to effectively blend the adapted prompt and vision features. The empirical study practices in two datasets: AIGIQA-20K (AI-Generated Image Quality Assessment database) and T2VQA-DB (Text-to-Video Quality Assessment DataBase), which validates the effectiveness of our proposed method: Prompt Condition Quality Assessment (PCQA). Our proposed simple and feasible framework may promote research development in the multimodal generation field.

关键词： Image quality Databases Large language models Semantics Quality assessment pattern recognition Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

BMAD: Benchmarks for Medical Anomaly Detection

BMAD: Benchmarks for Medical Anomaly Detection

引用

ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Jinan Bao Hanshi Sun Hanqiu Deng Yinsheng He Zhaoxiang Zhang Xingyu Li Electrical and Computer Engineering University of Alberta Electrical and Computer Engineering Carnegie Mellon University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Anomaly detection (AD) is a fundamental research problem in machine learning and computer vision, with practical applications in industrial inspection, video surveillance, and medical diagnosis. In the field of medical imaging, AD plays a crucial role in identifying anomalies that may indicate rare diseases or conditions. However, despite its importance, there is currently a lack of a universal and fair benchmark for evaluating AD methods on medical images, which hinders the development of more generalized and robust AD methods in this specific domain. To address this gap, we present a comprehensive evaluation benchmark for assessing AD methods on medical images. This benchmark consists of six reorganized datasets from five medical domains (i.e. brain MRI, liver CT, retinal OCT, chest X-ray, and digital histopathology) and three key evaluation metrics, and includes a total of fifteen state-of-the-art AD algorithms. This standardized and well-curated medical benchmark with the well-structured codebase enables researchers to easily compare and evaluate different AD methods, and ultimately leads to the development of more effective and robust AD algorithms for medical imaging. More information on BMAD is available in our GitHub repository: https://***/DorisBao/BMAD 1

关键词： computer vision Benchmark testing Video surveillance Retina pattern recognition Medical diagnosis Medical diagnostic imaging

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466页 << < 126 127 128 129 130 131 132 133 134 135 > >>

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：