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

5,349 篇 会议
129 册 图书
29 篇 期刊文献

馆藏范围

5,507 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,748 篇 工学
- 2,253 篇 计算机科学与技术...
- 926 篇 软件工程
- 478 篇 光学工程
- 399 篇 控制科学与工程
- 332 篇 机械工程
- 262 篇 仪器科学与技术
- 250 篇 信息与通信工程
- 128 篇 电气工程
- 122 篇 生物工程
- 90 篇 生物医学工程（可授...
- 70 篇 电子科学与技术（可...
- 39 篇 安全科学与工程
- 33 篇 化学工程与技术
- 31 篇 建筑学
- 27 篇 土木工程
- 25 篇 交通运输工程
- 24 篇 航空宇航科学与技...
859 篇 理学
- 526 篇 物理学
- 439 篇 数学
- 155 篇 统计学（可授理学、...
- 133 篇 生物学
- 28 篇 化学
- 22 篇 系统科学
242 篇 艺术学
- 242 篇 设计学（可授艺术学...
196 篇 管理学
- 101 篇 图书情报与档案管...
- 97 篇 管理科学与工程(可...
- 27 篇 工商管理
96 篇 医学
- 96 篇 临床医学
- 21 篇 基础医学(可授医学...
28 篇 法学
- 26 篇 社会学
8 篇 教育学
6 篇 经济学
5 篇 农学
2 篇 军事学

主题

2,165 篇 computer vision
915 篇 pattern recognit...
890 篇 conferences
640 篇 training
565 篇 cameras
410 篇 feature extracti...
373 篇 computational mo...
364 篇 image segmentati...
350 篇 visualization
338 篇 face recognition
321 篇 computer archite...
309 篇 robustness
290 篇 computer science
287 篇 shape
280 篇 humans
266 篇 object detection
234 篇 layout
196 篇 neural networks
191 篇 application soft...
191 篇 lighting

机构

20 篇 swiss fed inst t...
19 篇 institute for co...
18 篇 university of sc...
18 篇 microsoft resear...
18 篇 swiss fed inst t...
16 篇 carnegie mellon ...
16 篇 chinese acad sci...
14 篇 tsinghua univers...
14 篇 univ sci & techn...
14 篇 carnegie mellon ...
12 篇 harbin inst tech...
12 篇 tsinghua univ pe...
12 篇 department of co...
11 篇 megvii technol p...
11 篇 computer vision ...
11 篇 computer vision ...
10 篇 indian statistic...
10 篇 comp vis ctr bar...
10 篇 school of comput...
10 篇 univ modena & re...

作者

58 篇 timofte radu
17 篇 van gool luc
17 篇 luc van gool
17 篇 horst bischof
16 篇 rita cucchiara
16 篇 radu timofte
14 篇 escalera sergio
14 篇 bischof horst
14 篇 sergio escalera
13 篇 zhigang zhu
13 篇 hugo jair escala...
12 篇 murino vittorio
12 篇 li stan z.
12 篇 chen wei-ting
12 篇 qiang ji
11 篇 cucchiara rita
11 篇 fan haoqiang
11 篇 umapada pal
11 篇 marcos v. conde
11 篇 bowyer kevin w.

语言

5,493 篇 英文
10 篇 中文
5 篇 其他

检索条件"任意字段=2006 Conference on Computer Vision and Pattern Recognition Workshops"

共 5507 条记录，以下是821-830 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：

Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness

Renofeation: A Simple Transfer Learning Method for Improved ...

引用

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

作者： Chin, Ting-Wu Zhang, Cha Marculescu, Diana Carnegie Mellon Univ Pittsburgh PA 15213 USA Microsoft Cloud & AI Redmond WA USA Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9781665448994

Fine-tuning through knowledge transfer from a pre-trained model on a large-scale dataset is a widely spread approach to effectively build models on small-scale datasets. In this work, we show that a recent adversarial attack designed for transfer learning via re-training the last linear layer can successfully deceive models trained with transfer learning via end-to-end fine-tuning. This raises security concerns for many industrial applications. In contrast, models trained with random initialization without transfer are much more robust to such attacks, although these models often exhibit much lower accuracy. To this end, we propose noisy feature distillation, a new transfer learning method that trains a network from random initialization while achieving clean-data performance competitive with fine-tuning.

关键词： computer vision Computational modeling conferences Transfer learning Robustness pattern recognition Noise measurement

来源：评论

学校读者我要写书评

暂无评论

A Deep Adversarial Framework for Visually Explainable Periocular recognition

A Deep Adversarial Framework for Visually Explainable Perioc...

引用

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

作者： Brito, Joao Proenca, Hugo Univ Beira Interior IT Inst Telecomunicacoes P-6200001 Covilha Portugal

ISBN: (纸本)9781665448994

In the biometrics context, the ability to provide the reasoning behind a decision has been at the core of major research efforts. Explanations serve not only to increase the trust amongst the users of a system, but also to augment the system's overall accountability and transparency. In this work, we describe a periocular recognition framework that not only performs biometric recognition, but also provides visual representations of the features/regions that supported a decision. Being particularly designed to explain non-match ("impostors") decisions, our solution uses adversarial generative techniques to synthesise a large set of "genuine" image pairs, from where the most similar elements with respect to a query are retrieved. Then, assuming the alignment between the query/retrieved pairs, the element-wise differences between the query and a weighted average of the retrieved elements yields a visual explanation of the regions in the query pair that would have to be different to transform it into a "genuine" pair. Our quantitative and qualitative experiments validate the proposed solution, yielding recognition rates that are similar to the state-of-the-art, but - most importantly - also providing the visual explanations for every decision.

关键词： Visualization computer vision Biometrics (access control) conferences Transforms Cognition pattern recognition

来源：评论

学校读者我要写书评

暂无评论

PDAVIS: Bio-inspired Polarization Event Camera

PDAVIS: Bio-inspired Polarization Event Camera

引用

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

作者： Haessig, Germain Joubert, Damien Haque, Justin Milde, Moritz B. Delbruck, Tobi Gruev, Viktor Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria University of Zurich Institute of Neuroinformatics ETH Zurich Switzerland Western Sydney University International Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL United States

ISBN: (纸本)9798350302493

The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired frame-based cameras lack the high dynamic range and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12ms and dynamic range to ~72dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with submillisecond latencies over a millionfold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45°. Polarization information is reconstructed using both low-cost and low-latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image high dynamic range polarization scenes that vary at high speeds and to observe the dynamical properties of single collagen fibers in a bovine tendon under rapid cyclical ***: https://***/mFuCeTMWEqY © 2023 IEEE.

关键词： Polarization

来源：评论

学校读者我要写书评

暂无评论

HINet: Half Instance Normalization Network for Image Restoration

HINet: Half Instance Normalization Network for Image Restora...

引用

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

作者： Chen, Liangyu Lu, Xin Zhang, Jie Chu, Xiaojie Chen, Chengpeng MEGVII Technol Beijing Peoples R China Fudan Univ Shanghai Peoples R China Peking Univ Beijing Peoples R China

ISBN: (纸本)9781665448994

In this paper, we explore the role of Instance Normalization in low-level vision tasks. Specifically, we present a novel block: Half Instance Normalization Block (HIN Block), to boost the performance of image restoration networks. Based on HIN Block, we design a simple and powerful multi-stage network named HINet, which consists of two subnetworks. With the help of HIN Block, HINet surpasses the state-of-the-art (SOTA) on various image restoration tasks. For image denoising, we exceed it 0.11dB and 0.28 dB in PSNR on SIDD dataset, with only 7.5% and 30% of its multiplier-accumulator operations (MACs), 6.8 x and 2.9x speedup respectively. For image deblurring, we get comparable performance with 22.5% of its MACs and 3.3 x speedup on REDS and GoPro datasets. For image deraining, we exceed it by 0.3 dB in PSNR on the average result of multiple datasets with 1.4x speedup. With HINet, we won the 1st place on the NTIRE 2021 Image Deblurring Challenge - Track2. JPEG Artifacts, with a PSNR of 29.70.

关键词： Visualization computer vision conferences Transform coding Image restoration pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

FlowIBR: Leveraging Pre-Training for Efficient Neural Image-Based Rendering of Dynamic Scenes

FlowIBR: Leveraging Pre-Training for Efficient Neural Image-...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Marcel Büsching Josef Bengtson David Nilsson Mårten Björkman KTH Royal Insitute of Technology Chalmers University of Technology

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

We introduce FlowIBR, a novel approach for efficient monocular novel view synthesis of dynamic scenes. Existing techniques already show impressive rendering quality but tend to focus on optimization within a single scene without leveraging prior knowledge, resulting in long optimization times per scene. FlowIBR circumvents this limitation by integrating a neural image-based rendering method, pretrained on a large corpus of widely available static scenes, with a per-scene optimized scene flow field. Utilizing this flow field, we bend the camera rays to counteract the scene dynamics, thereby presenting the dynamic scene as if it were static to the rendering network. The proposed method reduces per-scene optimization time by an order of magnitude, achieving comparable rendering quality to existing methods — all on a single consumer-grade GPU.

关键词： computer vision conferences Graphics processing units Rendering (computer graphics) Cameras pattern recognition Optimization

来源：评论

学校读者我要写书评

暂无评论

Box-Level Tube Tracking and Refinement for Vehicles Anomaly Detection

Box-Level Tube Tracking and Refinement for Vehicles Anomaly ...

引用

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

作者： Wu, Jie Wang, Xionghui Xiao, Xuefeng Wang, Yitong ByteDance Inc Beijing Peoples R China

ISBN: (纸本)9781665448994

Traffic Anomaly detection is an essential computer vision task and plays a critical role in video structure analysis and urban traffic analysis. In this paper, we propose a box-level tracking and refinement algorithm to identify anomaly detection in road scenes. We first link the detection results to construct candidate spatio-temporal tubes via greedy search. Then the box-level refinement scheme is introduced to employ auxiliary detection cues to promote the abnormal predictions, which consists of spatial fusion, still-thing filter, temporal fusion, and feedforward optimization. Still-thing filter and feedforward optimization employ complementary detection concepts to promote the abnormal predictions, which helps determine an accurate abnormal period. The experimental results show that our approach is superior in the Traffic Anomaly Detection Track test set of the NVIDIA AI CITY 2021 CHALLENGE, which ranked second in this competition, with a 93.18% F1-score and 3.1623 root mean square error. It reveals that the proposed approach contributes to fine-grained anomaly detection in actual traffic accident scenarios and promoting the development of intelligent transportation.

关键词： computer vision Urban areas Transportation Electron tubes Artificial intelligence Vehicle dynamics Task analysis

来源：评论

学校读者我要写书评

暂无评论

Benchmarking Zero-Shot recognition with vision-Language Models: Challenges on Granularity and Specificity

Benchmarking Zero-Shot Recognition with Vision-Language Mode...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Zhenlin Xu Yi Zhu Siqi Deng Abhay Mittal Yanbei Chen Manchen Wang Paolo Favaro Joseph Tighe Davide Modolo AWS AI Labs Boson AI Meta

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

This paper presents novel benchmarks for evaluating vision-language models (VLMs) in zero-shot recognition, focusing on granularity and specificity. Although VLMs excel in tasks like image captioning, they face challenges in open-world settings. Our benchmarks test VLMs’ consistency in understanding concepts across semantic granularity levels and their response to varying text specificity. Findings show that VLMs favor moderately fine-grained concepts and struggle with specificity, often misjudging texts that differ from their training data. Extensive evaluations reveal limitations in current VLMs, particularly in distinguishing between correct and subtly incorrect descriptions. While fine-tuning offers some improvements, it doesn’t fully address these issues, highlighting the need for VLMs with enhanced generalization capabilities for real-world applications. This study provides insights into VLM limitations and suggests directions for developing more robust models.

关键词： computer vision Computational modeling Face recognition conferences Semantics Training data Focusing

来源：评论

学校读者我要写书评

暂无评论

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos

SoccerNet-v2: A Dataset and Benchmarks for Holistic Understa...

引用

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

作者： Deliege, Adrien Cioppa, Anthony Giancola, Silvio Seikavandi, Meisam J. Dueholm, Jacob, V Nasrollahi, Kamal Ghanem, Bernard Moeslund, Thomas B. Van Droogenbroeck, Marc Univ Liege Liege Belgium KAUST Thuwal Saudi Arabia Aalborg Univ Aalborg Denmark Milestone Syst Brondby Denmark

ISBN: (纸本)9781665448994

Understanding broadcast videos is a challenging task in computer vision, as it requires generic reasoning capabilities to appreciate the content offered by the video editing. In this work, we propose SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet [24] video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production. Specifically, we release around 300k annotations within SoccerNet's 500 untrimmed broadcast soccer videos. We extend current tasks in the realm of soccer to include action spotting, camera shot segmentation with boundary detection, and we define a novel replay grounding task. For each task, we provide and discuss benchmark results, reproducible with our open-source adapted implementations of the most relevant works in the field. SoccerNet-v2 is presented to the broader research community to help push computer vision closer to automatic solutions for more general video understanding and production purposes.

关键词： computer vision Annotations Grounding Production Benchmark testing Cameras pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Deep Video Codec Control for vision Models

Deep Video Codec Control for Vision Models

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Christoph Reich Biplob Debnath Deep Patel Tim Prangemeier Daniel Cremers Srimat Chakradhar NEC Laboratories America Inc. TU Munich TU Darmstadt Munich Center for Machine Learning (MCML)

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Standardized lossy video coding is at the core of almost all real-world video processing pipelines. Rate control is used to enable standard codecs to adapt to different network bandwidth conditions or storage constraints. However, standard video codecs (e.g., H.264) and their rate control modules aim to minimize video distortion w.r.t. human quality assessment. We demonstrate empirically that standard-coded videos vastly deteriorate the performance of deep vision models. To overcome the deterioration of vision performance, this paper presents the first end-to-end learnable deep video codec control that considers both bandwidth constraints and downstream deep vision performance, while adhering to existing standardization. We demonstrate that our approach better preserves downstream deep vision performance than traditional standard video coding.

关键词： Video coding Computational modeling Face recognition Pipelines Bandwidth Self-supervised learning Distortion

来源：评论

学校读者我要写书评

暂无评论

Leveraging Multi scale Backbone with Multilevel supervision for Thermal Image Super Resolution

Leveraging Multi scale Backbone with Multilevel supervision ...

引用

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

作者： Nathan, Sabari Kansal, Priya Couger Inc Shibuya Ku Tokyo Japan

ISBN: (纸本)9781665448994

This paper proposes an attention-based multi-level model with a multi-scale backbone for thermal image super-resolution. The model leverages the multi-scale backbone as well. The thermal image dataset is provided by PBVS 2020 in their thermal image super-resolution challenge. This dataset contains the images with three different resolution scales(low, medium, high) [1]. However, only the medium and high-resolution images are used to train the proposed architecture to generate the super-resolution images in x2, x4 scales. The proposed architecture is based on the Res2net blocks as the backbone of the network. Along with this, the coordinate convolution layer and dual attention are also used in the architecture. Further, multi-level supervision is implemented to supervise the output image resolution similarity with the real image at each block during training. To test the robustness of the proposed model, we evaluated our model on the Thermal-6 dataset [20]. The results show that our model is efficient to achieve state-of-the-art results on the PBVS dataset. Further the results on the Thermal-6 dataset show that the model has a decent generalization capacity.

关键词： Training Convolution conferences Superresolution computer architecture Robustness pattern recognition

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 << < 79 80 81 82 83 84 85 86 87 88 > >>

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：