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

2,958 篇 会议
39 篇 期刊文献
7 册 图书

馆藏范围

3,004 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,759 篇 工学
- 1,406 篇 计算机科学与技术...
- 685 篇 软件工程
- 489 篇 电气工程
- 396 篇 信息与通信工程
- 202 篇 控制科学与工程
- 130 篇 生物工程
- 78 篇 电子科学与技术（可...
- 65 篇 生物医学工程（可授...
- 58 篇 机械工程
- 54 篇 仪器科学与技术
- 49 篇 光学工程
- 33 篇 网络空间安全
- 30 篇 动力工程及工程热...
- 24 篇 安全科学与工程
- 23 篇 材料科学与工程（可...
- 22 篇 化学工程与技术
- 20 篇 测绘科学与技术
- 19 篇 石油与天然气工程
516 篇 理学
- 225 篇 物理学
- 189 篇 数学
- 143 篇 生物学
- 58 篇 统计学（可授理学、...
- 40 篇 系统科学
- 27 篇 化学
203 篇 管理学
- 135 篇 管理科学与工程(可...
- 81 篇 图书情报与档案管...
- 31 篇 工商管理
135 篇 医学
- 112 篇 临床医学
- 38 篇 基础医学(可授医学...
37 篇 法学
- 20 篇 社会学
18 篇 文学
14 篇 农学
10 篇 教育学
9 篇 经济学
2 篇 军事学

主题

590 篇 neural networks
173 篇 training
167 篇 artificial neura...
164 篇 deep learning
135 篇 computational mo...
124 篇 feature extracti...
115 篇 neural network
114 篇 convolutional ne...
88 篇 machine learning
87 篇 neurons
86 篇 parallel process...
79 篇 deep neural netw...
74 篇 computer archite...
73 篇 distributed comp...
65 篇 signal processin...
62 篇 distributed proc...
62 篇 accuracy
60 篇 recurrent neural...
55 篇 data models
49 篇 convolutional ne...

机构

11 篇 institute of inf...
9 篇 school of cyber ...
8 篇 univ chinese aca...
8 篇 natl univ def te...
7 篇 college of compu...
7 篇 carnegie mellon ...
7 篇 national laborat...
7 篇 beijing universi...
7 篇 natl univ def te...
6 篇 shanghai jiao to...
6 篇 the islamic univ...
6 篇 department of co...
5 篇 science and tech...
5 篇 ibm tj watson re...
5 篇 school of inform...
5 篇 king saud univer...
5 篇 shandong normal ...
5 篇 kaust thuwal
5 篇 university of ch...
5 篇 natl univ def te...

作者

8 篇 li dongsheng
8 篇 dou yong
8 篇 jie liu
6 篇 richtarik peter
6 篇 ribeiro alejandr...
6 篇 liu jie
6 篇 niu xin
6 篇 yong dou
6 篇 shulian yang
6 篇 zhang wei
5 篇 ryabinin max
5 篇 segarra santiago
5 篇 lai zhiquan
5 篇 ding bo
5 篇 qiao peng
5 篇 xu jiren
5 篇 kokkinos yiannis
5 篇 peng yuxing
5 篇 wang huaimin
5 篇 li aiping

语言

2,925 篇 英文
71 篇 其他
8 篇 中文
2 篇 土耳其文

检索条件"任意字段=Conference on Neural Network and Distributed Processing"

共 3004 条记录，以下是1361-1370 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：

Estimating the topology of neural networks from distributed observations 26

Estimating the topology of neural networks from distributed ...

引用

26th European Signal processing conference, EUSIPCO 2018

作者： Alexandru, Roxana Malhotra, Pranav Reynolds, Stephanie Luigi Dragotti, Pier Electrical and Electronic Engineering Department Imperial College London United Kingdom

ISBN: (纸本)9789082797015

We address the problem of estimating the effective connectivity of the brain network, using the input stimulus model proposed by Izhikevich in [1], which accurately reproduces the behaviour of spiking and bursting biological neurons, whilst ensuring computational simplicity. We first analyse the temporal dynamics of neural networks, showing that the spike propagation within the brain can be modelled as a diffusion process. This helps prove the suitability of NetRate algorithm proposed by Rodriguez in [2] to infer the structure of biological neural networks. Finally, we present simulation results using synthetic data to verify the performance of the topology estimation algorithm. © EURASIP 2018.

关键词： network topology

来源：评论

学校读者我要写书评

暂无评论

Path Planning and Moving Obstacle Avoidance with Neuromorphic Computing

Path Planning and Moving Obstacle Avoidance with Neuromorphi...

引用

IEEE International conference on Intelligence and Safety for Robotics (ISR)

作者： Motoki Sakurai Yosuke Ueno Masaaki Kondo The University of Tokyo RIKEN Center for Computational Science

Neuromorphic computing has been getting attention because of its potential for fast and low-power computation, robustness, and learning capability. Though traditional machine learning applications are main target of neuromorphic computing, its characteristic of parallel and distributed processing with simple spike-based signals is useful for other types of applications such as a shortest path finding problem (SPFP) on a graph. Prior work discussed approaches for mapping SPFP to a spiking neural network (SNN). In this paper, we propose an SNN algorithm for path planning with moving obstacles. In real world situation, there are many moving obstacles (such as other cars for an autonomous driving car and human for a moving robot) around a target agent which tries to optimize its own path to the goal. Finding an effective path in such an environment is not an easy task since behavior of obstacles is sometimes unknown and there must be a huge number of candidate paths to go. Traditional methods for SPFP with a general CPU may not be effective since it should compare candidate paths and select the most suitable one every time step. We consider two agents with SNN which tries to achieve two goals: “reaching its destination promptly” and “avoiding moving obstacles properly”. Thanks to SNN properties, the agent can learn and estimate how the obstacles move. We compare the proposal approaches with an existing method on a 2D grid graph and the result shows that the proposal agents can select proper paths depending on obstacles' movement.

关键词： Neuromorphic engineering Heuristic algorithms neural networks Path planning Robustness Safety Proposals

来源：评论

学校读者我要写书评

暂无评论

DeepPFCN: Deep Parallel Feature Consensus network for Person Re-identification 7th

DeepPFCN: Deep Parallel Feature Consensus Network for Person...

引用

7th National conference on Computer Vision, Pattern Recognition, Image processing, and Graphics, NCVPRIPG 2019

作者： Singh, Shubham Kumar Miyapuram, Krishna P. Raman, Shanmuganathan Indian Institute of Technology Gandhinagar PalajGujarat382355 India

ISBN: (纸本)9789811586965

Person re-identification aims to associate images of the same person over multiple non-overlapping camera views at different times. Depending on the human operator, manual re-identification in large camera networks is highly time consuming and erroneous. Automated person re-identification is required due to the extensive quantity of visual data produced by rapid inflation of large scale distributed multi-camera systems. The state-of-the-art works focus on learning and factorize person appearance features into latent discriminative factors at multiple semantic levels. We propose Deep Parallel Feature Consensus network (DeepPFCN), a novel network architecture that learns multi-scale person appearance features using convolutional neural networks. This model factorizes the visual appearance of a person into latent discriminative factors at multiple semantic levels. Finally consensus is built. The feature representations learned by DeepPFCN are more robust for the person re-identification task, as we learn discriminative scale-specific features and maximize multi-scale feature fusion selections in multi-scale image inputs. We further exploit average and max pooling in separate scale for person-specific task to discriminate features globally and locally. We demonstrate the re-identification advantages of the proposed DeepPFCN model over the state-of-the-art re-identification methods on three benchmark datasets - Market1501, DukeMTMCreID, and CUHK03. We have achieved mAP results of 75.8%, 64.3%, and 52.6% respectively on these benchmark datasets. © 2020, Springer Nature Singapore Pte Ltd.

关键词： network architecture

来源：评论

学校读者我要写书评

暂无评论

Automatic Construction of Tensor Product Variable Binding neural networks for neural-Symbolic Intelligent Systems

Automatic Construction of Tensor Product Variable Binding Ne...

引用

International conference on Electrical, Communication, and Computer Engineering (ICECCE)

作者： Alexander Demidovskij Higher School of Economics Nizhny Novgorod Russia

ISBN: (数字)9781728171166

ISBN: (纸本)9781728171173

One of the main challenges in building hybrid systems that integrate symbolic and sub-symbolic levels of computations is elaboration of methods that would allow expressing symbolic manipulations in a form of neural networks dynamics. In particular, it is extremely important to be able to process symbolic structures in a distributed format and perform analysis over this tensor representation that would be equivalent to a sequence of symbolic operations over the original structure. In this paper, the novel method is proposed for processing and analysis of semantics tree in a form of generated neural network. This method is built upon the Tensor Product Representations (TPRs) framework, scales well for an arbitrary structure and allows expressing simple symbolic operations in a form of neural network dynamics.

关键词： Tensile stress Task analysis Semantics Buildings Artificial neural networks Natural language processing

来源：评论

学校读者我要写书评

暂无评论

CWAI-CNER: Chinese entity recognition based on adaptive incorporation of characters and words

CWAI-CNER: Chinese entity recognition based on adaptive inco...

引用

Consumer Electronics and Computer Engineering (ICCECE), 2021 IEEE International conference on

作者： Pai Peng Xu Wu Xiaqing Xie Jingchen Wu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security BUPT Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security Beijing University of Posts and Telecommunications Library BUPT Beijing China

ISBN: (数字)9781728183190

ISBN: (纸本)9781728183206

Chinese Named Entity Recognition (CNER) is an important sub topic in the field of Chinese Natural Language processing, which plays an important role in multi tasks. However, it's difficult to determine the boundaries of entities in Chinese texts because the Chinese words are not naturally separated, which further causes the task of CNER much more difficult. In addition, the mainstream Named Entity Recognition (NER) is based on sequence tagging, which causes the cost of training set labeling very high, so many NER tasks are limited by training sets' deficiency. In this work, we propose a new CNER method based on adaptive incorporation of characters and words-CWAI to solve the problem of words information loss caused by lacking of words boundaries, which uses convolution neural network (CNN) to capture the local semantics for every character, and then adaptively calculates the weights of potential words that match a lexicon for each character based on attention mechanism between characters and words. And for the problem of limited model effects due to insufficient training set, we combined our model with pre-trained models to solve that.

关键词： Training Adaptation models Semantics Tagging Character recognition Task analysis Optimization

来源：评论

学校读者我要写书评

暂无评论

DNN-based distributed Multichannel Mask Estimation for Speech Enhancement in Microphone Arrays

DNN-based Distributed Multichannel Mask Estimation for Speec...

引用

IEEE International conference on Acoustics, Speech and Signal processing

作者： Nicolas Furnon Romain Serizel Irina Illina Slim Essid CNRS Inria Loria Université de Lorraine Nancy France LTCI Télécom Paris Institut Polytechnique de Paris Palaiseau France

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

Multichannel processing is widely used for speech enhancement but several limitations appear when trying to deploy these solutions in the real world. distributed sensor arrays that consider several devices with a few microphones is a viable solution which allows for exploiting the multiple devices equipped with microphones that we are using in our everyday life. In this context, we propose to extend the distributed adaptive node-specific signal estimation approach to a neural network framework. At each node, a local filtering is performed to send one signal to the other nodes where a mask is estimated by a neural network in order to compute a global multichannel Wiener filter. In an array of two nodes, we show that this additional signal can be leveraged to predict the masks and leads to better speech enhancement performance than when the mask estimation relies only on the local signals.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A mesh quality discrimination method based on convolutional neural network

A mesh quality discrimination method based on convolutional ...

引用

IEEE International conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Zhenpeng Xu Xinhai Chen Lihua Chi Jie Liu Chunye Gong Science and Technology on Parallel and Distributed Processing Laboratory & Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170060

With the rapid development of highperformance computing, computational fluid dynamics (CFD) has become an important part of hydrodynamics and aerodynamics. Mesh quality is the key factor that affects the accuracy and efficiency of CFD numerical calculation. However, the current the process of mesh quality discrimination is very time-consuming. The manpower time needed for this process takes up a large proportion in the whole numerical calculation process. A large number of artificial intelligence algorithms have been put forward to replace the human to efficiently complete all kinds of tedious tasks. In this paper, we propose a convolutional neural network (CNN) based mesh quality discrimination method, MeshNet. MeshNet uses residual neural network structure to learn mesh features and automatically judge the mesh quality. The experimental results show that the proposed network can greatly save labor time cost and achieve an accuracy of 94.41% for mesh quality discrimination.

关键词： Convolution Computational fluid dynamics Convolutional neural networks Jacobian matrices Artificial intelligence distributed processing Software engineering

来源：评论

学校读者我要写书评

暂无评论

An Implantable Wireless network of distributed Microscale Sensors for neural Applications 9

An Implantable Wireless Network of Distributed Microscale Se...

引用

9th IEEE/EMBS International conference on neural Engineering (NER)

作者： Lee, Jihun Mok, Ethan Huang, Jiannan Cui, Lingxiao Lee, Ah-Hyoung Leung, Vincent Mercier, Patrick Shellhammer, Steven Larson, Lawrence Asbeck, Peter Rao, Ramesh Song, Yoon-Kyu Nurmikko, Arto Laiwalla, Farah Brown Univ Providence RI 02906 USA Univ Calif San Diego La Jolla CA 92093 USA Seoul Natl Univ Seoul 08826 South Korea Qualcomm Inc San Diego CA 92121 USA

ISBN: (纸本)9781538679210

A vastly enhanced capability to bi-directionally interface with cortical microcircuits in a clinically viable way is the ultimate aspiration in neuroengineering. This necessitates a paradigm shift in neural interface system design beyond current bulky, monolithic constructs which are challenging to scale past 100-200 channels due to anatomic and engineering design constraints. A neural interface system relying on a spatially-distributed network of wireless microscale implantable sensors offers a highly scalable, robust and adaptive architecture for next-generation neural interfaces. We describe the development of a wireless network of sub-mm, untethered, individually addressable, fully wireless "Neurograin" sensors, in the context of an epicortical implant. Individual neurograin chiplets integrate a similar to 1 GHz wireless link for energy harvesting and telemetry with analog and digital electronics for neural signal amplification, on-chip storage, and networked communications via a TDMA protocol. Each neurograin thus forms a completely self-contained single channel of neural access and is implantable after post-process atomic layer deposition of thin-film (100 nm thick) barriers for hermetic sealing. Finally, ensembles of implantable neurograins form a fully wireless cortico-computer communication network (utilizing their unique device IDs). The implanted network is coordinated by a compact external "Epidermal Skinpatch" RF transceiver and data processing hub, which is implemented as a wearable module in order to be compatible with clinical implant considerations. We describe neurograin performance specifications and proof-of-concept in bench top and ex vivo and in vivo rodent platforms.

关键词： Wireless communication Wireless sensor networks Sensors Radio frequency Implants Time division multiple access Electrodes

来源：评论

学校读者我要写书评

暂无评论

DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters 33

DFNets: Spectral CNNs for Graphs with Feedback-Looped Filter...

引用

33rd conference on neural Information processing Systems (NeurIPS)

作者： Wijesinghe, Asiri Wang, Qing Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia

We propose a novel spectral convolutional neural network (CNN) model on graph structured data, namely distributed Feedback-Looped networks (DFNets). This model is incorporated with a robust class of spectral graph filters, called feedback-looped filters, to provide better localization on vertices, while still attaining fast convergence and linear memory requirements. Theoretically, feedback-looped filters can guarantee convergence w.r.t. a specified error bound, and be applied universally to any graph without knowing its structure. Furthermore, the propagation rule of this model can diversify features from the preceding layers to produce strong gradient flows. We have evaluated our model using two benchmark tasks: semi-supervised document classification on citation networks and semi-supervised entity classification on a knowledge graph. The experimental results show that our model considerably outperforms the state-of-the-art methods in both benchmark tasks over all datasets.

关键词： neural network models

来源：评论

学校读者我要写书评

暂无评论

Learning Hierarchical Graph for Occluded Pedestrian Detection 20

Learning Hierarchical Graph for Occluded Pedestrian Detectio...

引用

28th ACM International conference on Multimedia (MM)

作者： Li, Gang Li, Jian Zhang, Shanshan Yang, Jian Nanjing Univ Sci & Technol Nanjing Peoples R China Tencent Youtu Lab Shenzhen Peoples R China Nanjing Univ Sci & Technol PCA Lab Key Lab Intelligent Percept & Syst High Dimens In Minist Educ Nanjing Peoples R China Nanjing Univ Sci & Technol Jiangsu Key Lab Image & Video Understanding Socia Sch Comp Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9781450379885

Although pedestrian detection has made significant progress with the help of deep convolution neural networks, it is still a challenging problem to detect occluded pedestrians since the occluded ones can not provide sufficient information for classification and regression. In this paper, we propose a novel Hierarchical Graph Pedestrian Detector (HGPD), which integrates semantic and spatial relation information to construct two graphs named intra-proposal graph and inter-proposal graph, without relying on extra cues w.r.t visible regions. In order to capture the occlusion patterns and enhance features from visible regions, the intra-proposal graph considers body parts as nodes and assigns corresponding edge weights based on semantic relations between body parts. On the other hand, the inter-proposal graph adopts spatial relations between neighbouring proposals to provide additional proposal-wise context information for each proposal, which alleviates the lack of information caused by occlusion. We conduct extensive experiments on standard benchmarks of CityPersons and Caltech to demonstrate the effectiveness of our method. On CityPersons, our approach outperforms the baseline method by a large margin of 5.24pp on the heavy occlusion set, and surpasses all previous methods;on Caltech, we establish a new state of the art of 3.78% MR. Code is available at https://***/ligang-cs/PedestrianDetection-HGPD.

关键词： computer vision object detection occluded pedestrian detection graph neural networks

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301页 << < 133 134 135 136 137 138 139 140 141 142 > >>

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：