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

6,421 篇 会议
25 篇 期刊文献
3 册 图书

馆藏范围

6,448 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

3,849 篇 工学
- 3,647 篇 计算机科学与技术...
- 1,431 篇 软件工程
- 790 篇 光学工程
- 302 篇 信息与通信工程
- 242 篇 控制科学与工程
- 219 篇 电气工程
- 201 篇 机械工程
- 80 篇 生物医学工程（可授...
- 68 篇 生物工程
- 67 篇 电子科学与技术（可...
- 64 篇 仪器科学与技术
- 36 篇 建筑学
- 33 篇 力学（可授工学、理...
- 33 篇 土木工程
- 33 篇 航空宇航科学与技...
- 26 篇 安全科学与工程
- 22 篇 交通运输工程
- 20 篇 材料科学与工程（可...
- 18 篇 化学工程与技术
1,453 篇 理学
- 945 篇 物理学
- 890 篇 数学
- 352 篇 统计学（可授理学、...
- 134 篇 生物学
- 38 篇 系统科学
- 23 篇 化学
160 篇 管理学
- 110 篇 图书情报与档案管...
- 52 篇 管理科学与工程(可...
- 25 篇 工商管理
112 篇 医学
- 112 篇 临床医学
17 篇 法学
- 17 篇 社会学
12 篇 农学
8 篇 教育学
7 篇 艺术学
6 篇 经济学
2 篇 军事学

主题

2,288 篇 computer vision
789 篇 pattern recognit...
637 篇 cameras
629 篇 computer science
568 篇 face recognition
555 篇 layout
510 篇 image segmentati...
509 篇 conferences
498 篇 shape
445 篇 robustness
439 篇 object recogniti...
388 篇 humans
332 篇 feature extracti...
321 篇 training
303 篇 object detection
262 篇 image recognitio...
257 篇 application soft...
246 篇 lighting
238 篇 image reconstruc...
237 篇 computational mo...

机构

41 篇 microsoft resear...
26 篇 department of co...
21 篇 swiss fed inst t...
21 篇 school of comput...
20 篇 department of co...
19 篇 swiss fed inst t...
19 篇 carnegie mellon ...
18 篇 department of co...
17 篇 department of in...
17 篇 the robotics ins...
17 篇 institute of com...
16 篇 univ sci & techn...
16 篇 robotics institu...
15 篇 tsinghua univ pe...
14 篇 department of el...
14 篇 school of comput...
14 篇 school of comput...
13 篇 univ maryland co...
13 篇 microsoft resear...
13 篇 microsoft resear...

作者

39 篇 timofte radu
28 篇 s.k. nayar
24 篇 huang thomas s.
23 篇 xiaoou tang
22 篇 t. kanade
20 篇 t.s. huang
19 篇 van gool luc
19 篇 t. darrell
19 篇 chellappa rama
18 篇 nayar shree k.
17 篇 a.k. jain
17 篇 a. zisserman
17 篇 jain anil k.
16 篇 g. healey
16 篇 torralba antonio
16 篇 heung-yeung shum
16 篇 zisserman andrew
16 篇 l. van gool
15 篇 m. shah
15 篇 ji qiang

语言

6,447 篇 英文
2 篇 其他

检索条件"任意字段=1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992"

共 6449 条记录，以下是871-880 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：

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and ...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Bhat, Goutam Danelljan, Martin Timofte, Radu Akita, Kazutoshi Cho, Wooyeong Fan, Haoqiang Jia, Lanpeng Kim, Daeshik Lecouat, Bruno Li, Youwei Liu, Shuaicheng Liu, Ziluan Luo, Ziwei Maeda, Takahiro Mairal, Julien Micheloni, Christian Mo, Xuan Oba, Takeru Ostyakov, Pavel Ponce, Jean Son, Sanghyeok Sun, Jian Ukita, Norimichi Muhammad, Rao Yan, Umer Youliang Yu, Lei Zhussip, Magauiya Zou, Xueyi Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland Huawei Noahs Ark Lab Hong Kong Peoples R China Huawei CBG AITA Hong Kong Peoples R China Megvii Technol Beijing Peoples R China INRIA Rocquencourt France Toyota Technol Inst Toyota Japan Univ Udine Udine Italy KAIST Korea Adv Inst Sci & Technol Daejeon South Korea

ISBN: (纸本)9781665448994

This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times higher resolution. The challenge contained two tracks;Track 1 evaluating on synthetically generated data, and Track 2 using real-world bursts from mobile camera. In the final testing phase, 6 teams submitted results using a diverse set of solutions. The top-performing methods set a new state-of-the-art for the burst super-resolution task.

关键词： computer vision conferences Superresolution Merging Cameras pattern recognition Noise measurement

来源：评论

学校读者我要写书评

暂无评论

A Spacecraft Dataset for Detection, Segmentation and Parts recognition

A Spacecraft Dataset for Detection, Segmentation and Parts R...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Hoang Anh Dung Chen, Bo Chin, Tat-Jun Univ Adelaide Adelaide SA Australia

ISBN: (纸本)9781665448994

Virtually all aspects of modern life depend on space technology. Thanks to the great advancement of computer vision in general and deep learning-based techniques in particular, over the decades, the world witnessed the growing use of deep learning in solving problems for space applications, such as self-driving robot, tracers, insect-like robot on cosmos and health monitoring of spacecraft. These are just some prominent examples that has advanced space industry with the help of deep learning. However, the success of deep learning models requires a lot of training data in order to have decent performance, while on the other hand, there are very limited amount of publicly available space datasets for the training of deep learning models. Currently, there is no public datasets for space-based object detection or instance segmentation, partly because manually annotating object segmentation masks is very time consuming as they require pixel-level labelling, not to mention the challenge of obtaining images from space. In this paper, we aim to fill this gap by releasing a dataset for spacecraft detection, instance segmentation and part recognition. The main contribution of this work is the development of the dataset using images of space stations and satellites, with rich annotations including bounding boxes of spacecrafts and masks to the level of object parts, which are obtained with a mixture of automatic processes and manual efforts. We also provide evaluations with state-of-the-art methods in object detection and instance segmentation as a benchmark for the dataset. The link for downloading the proposed dataset can be found on https://***/Yurushia1998/SatelliteDataset.

关键词： Space vehicles Deep learning Image segmentation computer vision Satellites Service robots Object detection

来源：评论

学校读者我要写书评

暂无评论

A Cortically-inspired Architecture for Event-based Visual Motion Processing: From Design Principles to Real-world Applications

A Cortically-inspired Architecture for Event-based Visual Mo...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Peveri, Francesca Testa, Simone Sabatini, Silvio P. Univ Genoa Dept Informat Bioengn Robot & Syst Engn Via Opera Pia 11a Genoa Italy

ISBN: (纸本)9781665448994

We developed and tested the architecture of a bio-inspired Spiking Neural Network for motion estimation. The computation performed by the retina is emulated by the neuromorphic event-based image sensor DAVIS346 which constitutes the input of our network. We obtained neurons highly tuned to spatial frequency and orientation of the stimulus through a combination of feed-forward excitatory connections modeled as an elongated Gaussian kernel and recurrent inhibitory connections from two clusters of neurons within the same cortical layers. Sums over adjacent nodes weighted by time-variable synapses are used to attain Gabor-like spatio-temporal V1 receptive fields with selectivity to the stimulus' motion. In order to gain the invariance to the stimulus phase, the two polarities of the events provided by the neuromorphic sensor were exploited, which allowed us to build two pairs of quadrature filters from which we obtain Motion Energy detectors as described in [2]. Finally, a decoding stage allows us to compute optic flow from the Motion Detector layers. We tested the approach proposed with both synthetic and natural stimuli.

关键词： Visualization Neuromorphics Neurons Neural networks computer architecture Detectors Spatial filters

来源：评论

学校读者我要写书评

暂无评论

Do Deepfakes Feel Emotions? A Semantic Approach to Detecting Deepfakes Via Emotional Inconsistencies

Do Deepfakes Feel Emotions? A Semantic Approach to Detecting...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Hosler, Brian Salvi, Davide Murray, Anthony Antonacci, Fabio Bestagini, Paolo Tubaro, Stefano Stamm, Matthew C. Drexel Univ Dept Elect & Comp Engn Philadelphia PA 19104 USA Politecn Milan Dipartimento Elettron Informaz & Bioingn Milan Italy

ISBN: (纸本)9781665448994

Recent advances in deep learning and computer vision have spawned a new class of media forgeries known as deepfakes, which typically consist of artificially generated human faces or voices. The creation and distribution of deepfakes raise many legal and ethical concerns. As a result, the ability to distinguish between deepfakes and authentic media is vital. While deepfakes can create plausible video and audio, it may be challenging for them to to generate content that is consistent in terms of high-level semantic features, such as emotions. Unnatural displays of emotion, measured by features such as valence and arousal, can provide significant evidence that a video has been synthesized. In this paper, we propose a novel method for detecting deepfakes of a human speaker using the emotion predicted from the speaker's face and voice. The proposed technique leverages Long Short-Term Memory (LSTM) networks that predict emotion from audio and video Low-Level Descriptors (LLDs). Predicted emotion in time is used to classify videos as authentic or deepfakes through an additional supervised classifier.

关键词： computer vision Emotion recognition Law Semantics Speech recognition Media Forgery

来源：评论

学校读者我要写书评

暂无评论

EVSRNet: Efficient Video Super-Resolution with Neural Architecture Search

EVSRNet: Efficient Video Super-Resolution with Neural Archit...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Liu, Shaoli Zheng, Chengjian Lu, Kaidi Gao, Si Wang, Ning Wang, Bofei Zhang, Diankai Zhang, Xiaofeng Xu, Tianyu ZTE Corp State Key Lab Mobile Network & Mobile Multimedia Shenzhen Peoples R China

ISBN: (纸本)9781665448994

With the development of convolutional neural networks (CNN), the super-resolution results of CNN-based method have far surpassed traditional method. In particular, the CNN-based single image super-resolution method has achieved excellent results. Video sequences contain more abundant information compare with image, but there are few video super-resolution methods that can be applied to mobile devices due to the requirement of heavy computation, which limits the application of video super-resolution. In this work, we propose the Efficient Video Super-Resolution Network (EVSRNet) with neural architecture search for real-time video super-resolution. Extensive experiments show that our method achieves a good balance between quality and efficiency. Finally, we achieve a competitive result of 7.36 where the PSNR is 27.85 dB and the inference time is 11.3 ms/f on the target snapdragon 865 SoC, resulting in a 2nd place in the Mobile AI(MAI) 2021 real-time video super-resolution challenge. It is noteworthy that, our method is the fastest and significantly outperforms other competitors by large margins.

关键词： Visualization Superresolution Video sequences Neural networks computer architecture Streaming media Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Detecting and Matching Related Objects with One Proposal Multiple Predictions

Detecting and Matching Related Objects with One Proposal Mul...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Liu, Yang Hafemann, Luiz G. Jamieson, Michael Javan, Mehrsan Sportlogiq Montreal PQ Canada

ISBN: (纸本)9781665448994

Tracking players in sports videos is commonly done in a tracking-by-detection framework, first detecting players in each frame, and then performing association over time. While for some sports tracking players is sufficient for game analysis, sports like hockey, tennis and polo may require additional detections, that include the object the player is holding (e.g. racket, stick). The baseline solution for this problem involves detecting these objects as separate classes, and matching them to player detections based on the intersection over union (IoU). This approach, however, leads to poor matching performance in crowded situations, as it does not model the relationship between players and objects. In this paper, we propose a simple yet efficient way to detect and match players and related objects at once without extra cost, by considering an implicit association for prediction of multiple objects through the same proposal box. We evaluate the method on a dataset of broadcast ice hockey videos, and also a new public dataset we introduce called COCO +Torso. On the ice hockey dataset, the proposed method boosts matching performance from 57.1% to 81.4%, while also improving the meanAP of player+stick detections from 68.4% to 88.3%. On the COCO +Torso dataset, we see matching improving from 47.9% to 65.2%. The COCO +Torso dataset, code and pre-trained models will be released at https: //***/foreverYoungGitHub/detectand-match-related-objects.

关键词： computer vision conferences Games Detectors Ice Proposals pattern matching

来源：评论

学校读者我要写书评

暂无评论

Selective Replay Enhances Learning in Online Continual Analogical Reasoning

Selective Replay Enhances Learning in Online Continual Analo...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Hayes, Tyler L. Kanan, Christopher Rochester Inst Technol Rochester NY 14623 USA Paige Rochester NY USA Cornell Tech New York NY USA

ISBN: (纸本)9781665448994

In continual learning, a system learns from non-stationary data streams or batches without catastrophic forgetting. While this problem has been heavily studied in supervised image classification and reinforcement learning, continual learning in neural networks designed for abstract reasoning has not yet been studied. Here, we study continual learning of analogical reasoning. Analogical reasoning tests such as Raven's Progressive Matrices (RPMs) are commonly used to measure non-verbal abstract reasoning in humans, and recently offline neural networks for the RPM problem have been proposed. In this paper, we establish experimental baselines, protocols, and forward and backward transfer metrics to evaluate continual learners on RPMs. We employ experience replay to mitigate catastrophic forgetting. Prior work using replay for image classification tasks has found that selectively choosing the samples to replay offers little, if any, benefit over random selection. In contrast, we find that selective replay can significantly outperform random selection for the RPM task(1).

关键词： Measurement Protocols Neural networks Reinforcement learning Streaming media Cognition pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Indirect synthetic attack on thermal face biometric systems via visible-to-thermal spectrum conversion

Indirect synthetic attack on thermal face biometric systems ...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Mallat, Khawla Dugelay, Jean-Luc EURECOM Sophia Antipolis France

ISBN: (纸本)9781665448994

The growing interest in exploring thermal face biometrics is mostly due to the robustness of thermal imagery to face spoofing attacks. However, this robustness lies in the acquisition of thermal properties by the thermal sensor and is limited to presentation attacks. In this paper, we propose a new type of attack on thermal face recognition systems, performed at the post-sensor level. In the visible spectrum, this attack would be carried out by simply injecting a face image of the claimed identity into the communication channel right after the sensor. However, unlike visible face images that are abundantly available on the web, thermal face images are not easy to obtain. Therefore, we propose to generate synthetic thermal attacks by converting visible face images into the thermal spectrum. To perform visible-to-thermal spectrum conversion, we use a cascaded refinement network trained using contextual loss. In a scenario where the attacker has prior knowledge about the spoofing countermeasure of the system, we introduce a new loss computed at the local binary pattern (LBP) maps level to fool an LBP-based spoofing attack detection algorithm. The vulnerability of thermal face biometric systems to the proposed attack is then assessed using two existing baselines of spoofing attack detection. When compared to the challenging presentation attack using silicone masks, the equal error rate has increased from 0.20% to 11.60% and from 2.28% to 58.54% when exposed to the proposed synthetic attack, using the two spoofing attack detection baselines.

关键词： computer vision Error analysis Social networking (online) Face recognition conferences Communication channels Thermal sensors

来源：评论

学校读者我要写书评

暂无评论

Live Demo: E2P–Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P–Events to Polarization Reconstruction from P...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Tobi Delbruck Zuowen Wang Haiyang Mei Germain Haessig Damien Joubert Justin Haque Yingkai Chen Moritz B. Milde Viktor Gruev Sensors Group Institute of Neuroinformatics Univ. of Zurich and ETH Zurich Switzerland AIT Austrian Institute of Technology Center for Vision Automation & Control High-Performance Vision Systems Vienna Austria Intl. Centre for Neuromorphic Systems The MARCS Institute Western Sydney University Sydney Australia Dept. of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL USA

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main cvpr conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [...

关键词：

来源：评论

学校读者我要写书评

暂无评论

N-ROD: a Neuromorphic Dataset for Synthetic-to-Real Domain Adaptation

N-ROD: a Neuromorphic Dataset for Synthetic-to-Real Domain A...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Cannici, Marco Plizzari, Chiara Planamente, Mirco Ciccone, Marco Bottino, Andrea Caputo, Barbara Matteucci, Matteo Politecn Milan Milan Italy Politecn Torino Turin Italy Ist Italiano Tecnol Genoa Italy

ISBN: (纸本)9781665448994

Event cameras are novel neuromorphic sensors, which asynchronously capture pixel-level intensity changes in the form of "events". Event simulation from existing RGB datasets is commonly used to overcome the need of large amount of annotated data, which lacks due to the novelty of the event sensors. In this context, the possibility of using event simulation in synthetic scenarios, where data generation is not limited to pre-existing datasets, is to date still unexplored. In this work, we analyze the synth-to-real domain shift in event data, i.e., the gap arising between simulated events obtained from synthetic renderings and those captured with a real camera on real images. To this purpose, we extend to the event modality the popular RGB-D Object Dataset (ROD), which already comes with its synthetic version (SynROD). The resulting Neuromorphic ROD dataset (N-ROD) is the first to enable a synth-to-real analysis on event data, showing the effectiveness of Domain Adaptation techniques in reducing the synth-to-real shift. Moreover, through extensive experiments on multi-modal RGBE data, we show that events can be effectively combined with conventional visual information, encouraging further research in this area. The N-ROD dataset is available at https://***/home/.

关键词： Visualization computer vision Neuromorphics conferences Cameras Rendering (computer graphics) Data models

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 << < 84 85 86 87 88 89 90 91 92 93 > >>

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：