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

143 篇 会议
20 篇 期刊文献
2 册 图书

馆藏范围

165 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

127 篇 工学
- 102 篇 计算机科学与技术...
- 88 篇 软件工程
- 23 篇 控制科学与工程
- 22 篇 生物工程
- 19 篇 生物医学工程（可授...
- 15 篇 信息与通信工程
- 9 篇 机械工程
- 9 篇 光学工程
- 7 篇 电气工程
- 7 篇 化学工程与技术
- 6 篇 电子科学与技术（可...
- 5 篇 安全科学与工程
- 4 篇 仪器科学与技术
- 3 篇 动力工程及工程热...
- 3 篇 航空宇航科学与技...
- 2 篇 土木工程
57 篇 理学
- 24 篇 生物学
- 21 篇 数学
- 13 篇 物理学
- 9 篇 系统科学
- 7 篇 化学
- 6 篇 统计学（可授理学、...
35 篇 管理学
- 25 篇 图书情报与档案管...
- 14 篇 管理科学与工程(可...
- 10 篇 工商管理
16 篇 医学
- 16 篇 临床医学
- 13 篇 基础医学(可授医学...
- 10 篇 药学(可授医学、理...
10 篇 法学
- 10 篇 社会学
2 篇 教育学
- 2 篇 教育学
1 篇 经济学

主题

6 篇 human computer i...
4 篇 three-dimensiona...
4 篇 bacteriophages
4 篇 virtual reality
4 篇 user interfaces
3 篇 public policy
3 篇 computational mo...
3 篇 speech recogniti...
3 篇 visualization
3 篇 stochastic syste...
3 篇 artificial intel...
2 篇 3d interaction
2 篇 computer science
2 篇 information syst...
2 篇 support vector m...
2 篇 biomedical engin...
2 篇 computers and so...
2 篇 application soft...
2 篇 automation
2 篇 real time system...

机构

8 篇 human language t...
4 篇 department of ne...
4 篇 dept. of compute...
4 篇 human language t...
3 篇 department of ch...
3 篇 department of el...
3 篇 department of ne...
3 篇 paris brain inst...
3 篇 department of ra...
3 篇 department of ch...
3 篇 cea drf joliot n...
3 篇 national imaging...
3 篇 center of functi...
3 篇 biomedical engin...
3 篇 bio-imaging lab ...
3 篇 dept. of compute...
3 篇 radiology and ra...
3 篇 college of veter...
3 篇 department of co...
3 篇 human-computer i...

作者

16 篇 wu dekai
12 篇 saers markus
6 篇 bowman doug a.
6 篇 addanki karteek
5 篇 shneiderman ben
5 篇 bederson benjami...
4 篇 tungare manas
3 篇 zhang jiangyang
3 篇 won c.h.
3 篇 johnson jeff
3 篇 wu dan
3 篇 choi h.c.
3 篇 ben shneiderman
3 篇 michielse stijn
3 篇 drobnjak ivana
3 篇 plaisant catheri...
3 篇 grant samuel c.
3 篇 hertanu andreea
3 篇 hochheiser harry
3 篇 shemesh noam

语言

157 篇 英文
8 篇 其他

检索条件"机构=Center for Human-Computer Interaction and Dept. of Computer Science"

共 165 条记录，以下是21-30 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：

Material manifestations of dislocation and (Re)connection 17

Material manifestations of dislocation and (Re)connection

引用

17th European Conference on computer Supported Cooperative Work, ECSCW 2019

作者： Smit, Dorothé Krischkowsky, Alina Beuthel, Janne Mascha Maurer, Bernhard Fuchsberger, Verena Murer, Martin Tscheligi, Manfred Devendorf, Laura Zaman, Bieke Nouwen, Marije Aal, Konstantin Center for Human-Computer Interaction University of Salzburg Austria ATLAS Institute Dept. of Information Science University of Colorado United States KU Leuven Belgium Institute for Information Systems and New Media University of Siegen Germany

This workshop focuses on the material qualities of dislocation. The process of humans becoming separated from each other is likely to have diverse consequences;from shifting frequency, modes, or routines of communication and collaboration, to completely alternate means of connection. In this workshop, we aim to discuss a broad range of material manifestations and implications of (researching and designing for) dislocation. While engaging with material qualities of dislocation, we will reflect on the state of the art, discuss research gaps and potentials, and explore hands-on how design can create opportunities for (re)connection in response to dislocation through the creation of tangible interfaces. © 2019 held by Authors.

关键词： Interface states

来源：评论

学校读者我要写书评

暂无评论

Grid-Search Integrated Optimized Support Vector Machine Model for Breast Cancer Detection

Grid-Search Integrated Optimized Support Vector Machine Mode...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Partho Ghose Selina Sharmin Loveleen Gaur Zhongming Zhao Dept. Computer Science and Engineering Jagannath University Dhaka Bangladesh Amity International Business School Amity University Noida India Human Genetics Center School of Public Health The University of Texas Health Science Center at Houston Houston TX USA

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Breast cancer is a common and highly heterogeneous cancer worldwide. Rapid detection and early diagnosis are essential in its treatment, but it is challenging due to mammogram’s uncertainty. Based on machine learning, operative clinical systems can be implemented to save patients’ lives. This study proposes an optimized support vector machine (SVM) model to predict breast cancer using the grid search method to find the best hyper-parameters. For validation, we offer an in-dept. experimental study and we achieve, for Benign|Malignant|Average cases, accuracy of 98.69%|99.72%|99.0%, precision of 96.0%|100.0%|98.0%, recall of 100.0%|98.0%|98.0%, and Fl-score of 98.0%|97.0%|98.0% respectively. Comparison is made between the tuned hyper-parameter and default hyper-parameter performance. SVM performance with default parameters is 96%, while the maximum accuracy is achieved by hyper-parameters tuned. An SVM model is 99%, which can be a better cancer detection system. The results show performance improves when the best hyperparameters are used for SVM training. Thus, the analysis and comparison indicate that our stated system is better than the state-of-the-art ML-based breast cancer detection system.

关键词： Support vector machines Uncertainty Search methods Biological system modeling Medical services Machine learning Predictive models

来源：评论

学校读者我要写书评

暂无评论

Sensors Technologies for human Activity Analysis Based on SVM Optimized by PSO Algorithm

Sensors Technologies for Human Activity Analysis Based on SV...

引用

2019 International Conference on Applied and Engineering Mathematics, ICAEM 2019

作者： Batool, Mouazma Jalal, Ahmad Kim, Kibum Dept. of Computer Science Air University Islamabad Pakistan Dept. of Human-Computer Interaction Hanyang University Seoul Korea Republic of

ISBN: (纸本)9781728123530

The rapid growth of wearable sensors have increased the importance of human activity analysis in different areas of information technologies. Motion artifacts often degrade the performance of wearable sensors. Several wearable sensors have been used since the last decades in order to recognize physical activity detection. The wearable sensors could have numerous applications in medical and daily life routine activities like human gait analysis, health care, fitness, etc. In this paper, accelerometer and gyroscope sensors dataset has been used to propose an efficient model for physical activity detection. We designed a new feature extraction algorithm, Mel-frequency cepstral coefficient and statistical features to extract valuable features. Then, classification of different daily life activities is performed via Particle Swarm Optimization (PSO) together with SVM algorithm over bench mark motion-sense dataset. The results of our model shows that pre-classifier as PSO and SVM along with feature extraction module excel in term of accuracy and efficiency. Our experimental results have shown accuracy of 87.50% over motion-sense dataset. This model is recommended for the system associating in physical activity detection, especially in medical fitness field. © 2019 IEEE.

关键词： Wearable sensors

来源：评论

学校读者我要写书评

暂无评论

Region and decision tree-based segmentations for multi-objects detection and classification in outdoor scenes 17

Region and decision tree-based segmentations for multi-objec...

引用

17th International Conference on Frontiers of Information Technology, FIT 2019

作者： Ahmed, Abrar Jalal, Ahmad Kim, Kibum Dept. of Computer Science Air University Islamabad Pakistan Dept. of Human-Computer Interaction Hanyang University Seoul Korea Republic of

ISBN: (纸本)9781728166254

Accurate segmentation and detection of all mixed and occluded objects in the complex indoor/outdoor scenes become a vital topic of computer vision. These above-mentioned scenarios are the significant part of important vision applications such as autonomous driving, traffic monitoring, security surveillance, humane body parts detection, objects tracking and scene recognition. It is still difficult to accurately detect all the objects in the image due to illumination changes, occlusion and different directions. Meanwhile, segmenting the image in parts helps to detect the multi objects accurately. In this paper, we designed a system having improved techniques for the accurate segmentation and detection of multi objects. Firstly, we have combined the results of two methods for accurate segmentation of multiple objects, (i) Decision trees for labeling every neighboring pixel and assigning a separate color to all object present in complex images and (ii) Region-based segmentation for significant detection of multiple regions and drawing boundaries of all objects. Secondly, detection is performed by searching the objects with previously assigned colors. Finally, we have performed labeling with class name to all objects present in the images. We have performed our experimental over two benchmarked datasets as Instance Saliency images and MSRC. Our experimental work has shown improved results with respect to other state of the art algorithms. © 2019 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Multi-Person Tracking in Smart Surveillance System for Crowd Counting and Normal/Abnormal Events Detection

Multi-Person Tracking in Smart Surveillance System for Crowd...

引用

2019 International Conference on Applied and Engineering Mathematics, ICAEM 2019

作者： Shehzed, Ahsan Jalal, Ahmad Kim, Kibum Dept. of Computer Science Air University Islamabad Pakistan Dept. of Human-Computer Interaction Hanyang University Seoul Korea Republic of

ISBN: (纸本)9781728123530

Automated video surveillance addresses people's real-time observation to describe their behaviors and interactions. This paper presents a novel multi-person tracking system for crowd counting and normal/abnormal events detection at indoor/outdoor surveillance environments. The proposed system consists of four modules: people detection, head-torso template extraction, tracking and crowd cluster analysis. Firstly, the system extracts human silhouettes using inverse transform as well as median filter reducing the cost of computing and handling various complex monitoring situations. Secondly, people are detected by their head torso due to less varied and hardly occluded. Thirdly, each person is tracked through consecutive frames using the Kalman filter techniques with Jaccard similarity and normalized cross-correlation. Finally, the template marking is used for crowd counting having cues localization and clustered via Gaussian mapping for normal/abnormal events detection. The experimental results on two challenging datasets of video surveillance such as PETS2009 and UMN crowd analysis datasets demonstrate that the proposed system provides 88.7% and 95.5% in terms of counting accuracy and detection rate. © 2019 IEEE.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models

Scalable Event-by-Event Processing of Neuromorphic Sensory S...

引用

Neuromorphic Systems (ICONS), International Conference on

作者： Mark Schöne Neeraj Mohan Sushma Jingyue Zhuge Christian Mayr Anand Subramoney David Kappel Chair of Highly-Parallel VLSI-Systems and Neuro-Microelectronics TU Dresden Dresden Germany Ruhr University Bochum Institut für Neuroinformatik Germany Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) TU Dresden Dresden Germany Centre for Tactile Internet (CeTI) with Human-in-the-Loop TU Dresden Dresden Germany Dept. of Computer Science Royal Holloway University of London Egham United Kingdom

ISBN: (数字)9798350368659

ISBN: (纸本)9798350368666

Event-based sensors feature valuable properties for real-time processing such as fast response times and encoding of the sensory data as successive temporal differences. However, most current methods either collapse events into frames, therefore suppressing these properties, or cannot scale up when processing the event data directly event-by-event. In this work, we address the key challenges of scaling up event-by-event modeling of the long event streams emitted by such sensors, which is a particularly relevant problem for neuromorphic computing. While prior methods can process up to a few thousand time steps, our model, based on modern recurrent deep state-space models, scales to event streams of millions of events for both training and inference. We leverage their stable parameterization for learning long-range dependencies, parallelizability along the sequence dimension, and their ability to integrate asynchronous events effectively to scale them up to long event streams. We further augment these with novel event-centric techniques enabling our model to match or beat the state-of-the-art performance on several event stream benchmarks. In the Spiking Speech Commands task, we improve state-of-the-art by a large margin of 7.7 % to 88.4 %. On the DVS128-Gestures dataset, we achieve competitive results without using frames or convolutional neural networks. Our work demonstrates, for the first time, that it is possible to use fully event-based processing with purely recurrent networks to achieve state-of-the-art task performance in several event-based benchmarks.

关键词： Training Event detection Computational modeling Benchmark testing Sensor systems Real-time systems Sensors State-space methods Time factors Streams

来源：评论

学校读者我要写书评

暂无评论

Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models

Weight Sparsity Complements Activity Sparsity in Neuromorphi...

引用

Neuromorphic Systems (ICONS), International Conference on

作者： Rishav Mukherji Mark Schöne Khaleelulla Khan Nazeer Christian Mayr David Kappel Anand Subramoney Birla Institute of Technology and Science Pilani - Goa Campus Goa India Chair of Highly-Parallel VLSI-Systems and Neuro-Microelectronics TU Dresden Dresden Germany Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) TU Dresden Dresden Germany Centre for Tactile Internet (CeTI) with Human-in-the-Loop TU Dresden Dresden Germany Ruhr University Bochum Institut für Neuroinformatik Germany Dept. of Computer Science Royal Holloway University of London Egham United Kingdom

ISBN: (数字)9798350368659

ISBN: (纸本)9798350368666

Activity and parameter sparsity are two standard methods of making neural networks computationally more efficient. Event-based architectures such as spiking neural networks (SNNs) naturally exhibit activity sparsity, and many methods exist to sparsify their connectivity by pruning weights. While the effect of weight pruning on feed-forward SNNs has been previously studied for computer vision tasks, the effects of pruning for complex sequence tasks like language modeling are less well studied since SNNs have traditionally struggled to achieve meaningful performance on these tasks. Using a recently published SNN-like architecture that works well on small-scale language modeling, we study the effects of weight pruning when combined with activity sparsity. Specifically, we study the tradeoff between the multiplicative efficiency gains the combination affords and its effect on task performance for language modeling. To dissect the effects of the two sparsities, we conduct a comparative analysis between densely activated models and sparsely activated event-based models across varying degrees of connectivity sparsity. We demonstrate that sparse activity and sparse connectivity complement each other without a proportional drop in task performance for an event-based neural network trained on the Penn Treebank and WikiText-2 language modeling datasets. Our results suggest sparsely connected event-based neural networks are promising candidates for effective and efficient sequence modeling.

关键词： Analytical models computer vision Event detection Neuromorphics Computational modeling Neural networks computer architecture Spiking neural networks Computational efficiency Standards

来源：评论

学校读者我要写书评

暂无评论

Cognitive ergonomics on the move: Art ecosystems are a new application domain

Cognitive ergonomics on the move: Art ecosystems are a new a...

引用

2019 International Workshop on Rethinking Cognitive Ergonomics, ReCogErg 2019

作者： Li, Danzhu van der Veer, Gerrit Dept. Human-Media Interaction Twente University Enschede Netherlands Multimedia and Culture Dept. Computer Science Vrije Universiteit Amsterdam Netherlands Dept. Multimedia and Animation Luxun Academy of Fine Arts Liaoning China

The unprecedented state of contemporary art is due to the integration of advanced science and technology. The complementary and coordinated development of art and technology is expected to gradually revolutionize people's traditional perceptions in a wide range of art domains. This revolution belongs to artists as well as to the increasingly different types of other stakeholders. This paper explores the changing process of the role of cognitive ergonomics in aesthetic creation, participation, and experience. The value of experience as component of CE for the modern art domain is discussed. Copyright © 2019 for this paper by its authors.

关键词： Ecosystems

来源：评论

学校读者我要写书评

暂无评论

Categorical timeline allocation and alignment for diagnostic head movement tracking feature analysis 32

Categorical timeline allocation and alignment for diagnostic...

引用

32nd IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2019

作者： Ogihara, Mitsunori Hammal, Zakia Martin, Katherine B. Cohn, Jeffrey F. Cassell, Justine Ren, Gang Messinger, Daniel S. Dept. Computer Science University of Miami United States Robotics Institute Carnegie Mellon University United States Tobii Pro Dept. Psychology University of Pittsburgh United States Human-Computer Interaction Institute Carnegie Mellon University United States Ctr. Comp. Science University of Miami United States Dept. Psychology University of Miami United States

ISBN: (纸本)9781728125060

Atypical head movement pattern characterization is a potentially important cue for identifying children with autism spectrum disorder. In this paper, we implemented a computational framework for extracting the temporal patterns of head movement and utilizing the imbalance of temporal pattern distribution between diagnostic categories (e.g., children with or without autism spectrum disorder) as potential diagnostic cues. The timeline analysis results show a large number of temporal patterns with significant imbalances between diagnostic categories. The temporal patterns show strong classification power on discriminative and predictive analysis metrics. The long time-span temporal patterns (e.g., patterns spanning 15-30 sec.) exhibit stronger discriminative capabilities compared with the temporal patterns with relatively shorter time spans. Temporal patterns with high coverage ratios (existing in a large portion of the video durations) also show high discriminative capacity. © 2019 IEEE computer Society. All rights reserved.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Region and Decision Tree-Based Segmentations for Multi-Objects Detection and Classification in Outdoor Scenes

Region and Decision Tree-Based Segmentations for Multi-Objec...

引用

Frontiers of Information Technology (FIT)

作者： Abrar Ahmed Ahmad Jalal Kibum Kim Dept. of Computer Science Air University Islamabad Pakistan Dept. of Human-Computer Interaction Hanyang University Seoul South Korea

ISBN: (数字)9781728166254

ISBN: (纸本)9781728166261

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17页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：