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

2,959 篇 会议
39 篇 期刊文献
7 册 图书

馆藏范围

3,005 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,760 篇 工学
- 1,407 篇 计算机科学与技术...
- 684 篇 软件工程
- 490 篇 电气工程
- 397 篇 信息与通信工程
- 203 篇 控制科学与工程
- 130 篇 生物工程
- 79 篇 电子科学与技术（可...
- 65 篇 生物医学工程（可授...
- 59 篇 机械工程
- 54 篇 仪器科学与技术
- 49 篇 光学工程
- 34 篇 网络空间安全
- 30 篇 动力工程及工程热...
- 24 篇 材料科学与工程（可...
- 24 篇 安全科学与工程
- 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
517 篇 理学
- 226 篇 物理学
- 190 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
168 篇 artificial neura...
165 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
50 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
72 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 3005 条记录，以下是1071-1080 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：

2nd International conference on Sensor networks and Signal processing, SNSP 2019

2nd International Conference on Sensor Networks and Signal P...

引用

2nd International conference on Sensor networks and Signal processing, SNSP 2019

ISBN: (纸本)9789811549168

The proceedings contain 42 papers. The special focus in this conference is on Sensor networks and Signal processing. The topics include: Graphic qr code with the second hidden qr code by codeword rearrangement;a novel position-shift method of double-phase fresnel hologram for synthesizing a complex fresnel hologram;an examination of obstacle avoidance by sound for visually impaired children;efficient technique of impulsive noise detection and replacement in color digital images;development of walking support system for visually impaired people;research on video mosaic technology based on fully mechanized face of coal mine;optimization scheme for traceability of distributed denial of service attacks based on dynamic probability packet marking;processing initial data for the agent-based model of the russian federation spatial development;design and implementation of total station wireless data transmission system;improvement of rpl routing strategy based on 6lowpan;the comprehensive evaluation of "five aspects" based on coefficient-of-variation-modified g1 combination weighting;an inertia weight variable particle swarm optimization algorithm with mutation;performance of probabilistic approach and artificial neural network on questionnaire data concerning taiwanese ecotourism;ac operation hardware learning neural circuit using v-f converter system;an inequality for linear canonical transform;a general approach to probabilistic data mining;a novel four-dimensional chaotic system with four cross terms;influence of the optical aspects of photographic composition on the user experience in the issues related to decision making, choices and level of visual comfort;compositional models: iterative structure learning from data;computer vision-based demersal fish length measurement technology.

关键词：

来源：评论

学校读者我要写书评

暂无评论

network-based synchronous control of memristive neural networks with denial of service attacks 39

Network-based synchronous control of memristive neural netwo...

引用

39th Chinese Control conference (CCC)

作者： Cai, Xinyu Zhang, Yijun Jiang, Zhcnpeng Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China

ISBN: (数字)9789881563903

ISBN: (纸本)9789881563903

This letter is concerned with the issue of global asymptotically synchronization of two neural networks with the denial of service attacks in the communication channels. The memristive neural networks which are with memory, adaptability and high parallel processing ability are considered, A master-slave framework with networks attacks are proposed. Compared with the prior literatures, the DoS attack, which can destroy the network conununication, has been modeled by Bernoulli distributed variable. Some sufficient conditions are derived to ensure the synchronization of networks by using Lyapunov function approach. Finally, a numerical example is given to illustrate the effectiveness of obtained results.

关键词： Memristive neural networks Synchronization DoS attacks network-based

来源：评论

学校读者我要写书评

暂无评论

17th IFIP WG 10.3 International conference on network and Parallel Computing, NPC 2020

17th IFIP WG 10.3 International Conference on Network and Pa...

引用

17th IFIP WG 10.3 International conference on network and Parallel Computing, NPC 2020

ISBN: (纸本)9783030794774

The proceedings contain 39 papers. The special focus in this conference is on network and Parallel Computing. The topics include: LCache: Machine Learning-Enabled Cache Management in Near-Data processing-Based Solid-State Disks;security Situation Prediction of network Based on Lstm neural network;Dynamic GMMU Bypass for Address Translation in Multi-GPU Systems;Parallel Fast DOA Estimation Algorithm Based on SML and Membrane Computing;segmented Merge: A New Primitive for Parallel Sparse Matrix Computations;a Hierarchical Model of Control Logic for Simplifying Complex networks Protocol Design;FPGA-Based Multi-precision Architecture for Accelerating Large-Scale Floating-Point Matrix Computing;a Configurable Hardware Architecture for Runtime Application of network Calculus;FEB3D : An Efficient FPGA-Accelerated Compression Framework for Microscopy Images;A Dynamic Mapping Model for General CNN Accelerator Based on FPGA;NUMA-Aware Optimization of Sparse Matrix-Vector Multiplication on ARMv8-Based Many-Core Architectures;CARAM: A Content-Aware Hybrid PCM/DRAM Main Memory System Framework;Optimization of RDMA-Based HDFS Data Distribution Mechanism;reducing the Time of Live Container Migration in a Workflow;RDMA-Based Apache Storm for High-Performance Stream Data processing;payment Behavior Prediction and Statistical Analysis for Shared Parking Lots;location-Based Service Recommendation for Cold-Start in Mobile Edge Computing;an Adaptive Delay-Limited Offloading Scheme Based on Multi-round Auction Model for Mobile Edge Computing;an Efficient Data Transmission Strategy for Edge-Computing-Based Opportunistic Social networks;shadow Data: A Method to Optimize Incremental Synchronization in Data Center;A Dynamic Protection Mechanism for GPU Memory Overflow;DROAllocator: A Dynamic Resource-Aware Operator Allocation Framework in distributed Streaming processing;a Medical Support System for Prostate Cancer Based on Ensemble Method in Developing Countries.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Fully-integrated Gesture and Gait processing SoC for Rehabilitation with ADC-less Mixed-signal Feature Extraction and Deep neural network for Classification and Online Training

A Fully-integrated Gesture and Gait Processing SoC for Rehab...

引用

IEEE Custom Integrated Circuits conference (CICC)

作者： Wei, Yijie Cao, Qiankai Gu, Jie Otseidu, Kofi Hargrove, Levi Northwestern Univ Dept Elect & Comp Engn Evanston IL 60208 USA Intel Corp Hudson MA USA Shirley Ryan Abil Lab Chicago IL USA

ISBN: (纸本)9781728160313

An ultra-low-power gesture and gait classification SoC is presented for rehabilitation application featuring (1) mixed-signal feature extraction and integrated low-noise amplifier eliminating expensive ADC and digital feature extraction, (2) an integrated distributed deep neural network (DNN) ASIC supporting a scalable multi-chip neural network for sensor fusion with distortion resiliency for low-cost front end modules, (3) on-chip learning of DNN engine allowing in-situ training of user specific operations. A 12-channel 65nm CMOS test chip was fabricated with 1 mu W power per channel, less than 3ms computation latency, on-chip training for user-specific DNN model and multi-chip networking capability.

关键词： edge processing deep neural network inter-chip communication mixed-signal feature extraction on-chip learning

来源：评论

学校读者我要写书评

暂无评论

Stannis: Low-Power Acceleration of DNN Training Using Computational Storage Devices 57

Stannis: Low-Power Acceleration of DNN Training Using Comput...

引用

57th ACM/IEEE Design Automation conference (DAC)

作者： HeydariGorji, Ali Torabzadehkashi, Mahdi Rezaei, Siavash Bobarshad, Hossein Alves, Vladimir Chou, Pai H. UC Irvine Irvine CA 92697 USA NGD Syst Inc Irvine CA USA

ISBN: (数字)9781728110851

ISBN: (纸本)9781728110851

Computational storage devices enable in-storage processing of data in place. These devices contain 64-bit application processors and hardware accelerators that can help improving performance and saving power by reducing or eliminating data movement between host computers and storage units. This paper proposes a framework, named Stannis, for distributed in-storage training of deep neural networks on clusters of computational storage devices. This in-storage processing style of training ensures that private data never leaves the storage while fully controlling the public sharing of data. The Stannis framework distributes the workload based on the processing power of each worker by determining the proper batch size for each node. Stannis also ensures the availability of input data for all nodes to avoid rank stall while maximizing the utilization and overall processing speed. Experimental results show up to 2.7x speedup and 69% reduction in energy consumption with no significant loss in accuracy.

关键词： distributed deep neural network training training distribution task parallelization computational storage near data processing privacy

来源：评论

学校读者我要写书评

暂无评论

FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous neural networks 22

FedClassAvg: Local Representation Learning for Personalized ...

引用

Proceedings of the 51st International conference on Parallel processing

作者： Jaehee Jang Heoneok Ha Dahuin Jung Sungroh Yoon Department of Electrical and Computer Engineering Seoul National University Republic of Korea Department of Electrical and Computer Engineering and Interdisciplinary Program in Artificial Intelligence Seoul National University Republic of Korea and AIIS ASRI and INMC Seoul National University Republic of Korea

ISBN: (纸本)9781450397339

Personalized federated learning is aimed at allowing numerous clients to train personalized models while participating in collaborative training in a communication-efficient manner without exchanging private data. However, many personalized federated learning algorithms assume that clients have the same neural network architecture, and those for heterogeneous models remain understudied. In this study, we propose a novel personalized federated learning method called federated classifier averaging (FedClassAvg). Deep neural networks for supervised learning tasks consist of feature extractor and classifier layers. FedClassAvg aggregates classifier weights as an agreement on decision boundaries on feature spaces so that clients with not independently and identically distributed (non-iid) data can learn about scarce labels. In addition, local feature representation learning is applied to stabilize the decision boundaries and improve the local feature extraction capabilities for clients. While the existing methods require the collection of auxiliary data or model weights to generate a counterpart, FedClassAvg only requires clients to communicate with a couple of fully connected layers, which is highly communication-efficient. Moreover, FedClassAvg does not require extra optimization problems such as knowledge transfer, which requires intensive computation overhead. We evaluated FedClassAvg through extensive experiments and demonstrated it outperforms the current state-of-the-art algorithms on heterogeneous personalized federated learning tasks.

关键词： Communication Efficient Resource Constraint Representation Learning neural networks Model Heterogeneity Federated Learning

来源：评论

学校读者我要写书评

暂无评论

2021 IEEE 13th International conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2021

2021 IEEE 13th International Conference on Humanoid, Nanotec...

引用

2021 IEEE 13th International conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2021

ISBN: (纸本)9781665401678

The proceedings contain 218 papers. The topics discussed include: smart electronic assistive device for visually impaired individual through image processing;deriving heart rate and respiratory rate from pulse oximetry using neural networks;classification of Filipino Braille codes with contractions using machine vision;behavior-based early cervical cancer risk detection using artificial neural networks;reverse vending machine with power output for mobile devices using vision – based system;study on seedling disc pellets made from rice straw and cow manure;development and characterization of energy harvester using electromagnetic linear generators in bicycle shock absorbers;precision agriculture detecting npk level using a wireless sensor network with mobile sensor nodes;steady state estimation of power distribution networks with distributed generation using integrated dc load flow and weighted least-square algorithm;and waste to energy technologies using multi-criteria decision analysis for municipal solid waste management in Manila City, Philippines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

BGElasor: Elastic-Scaling Framework for distributed Streaming processing with Deep neural network 16th

BGElasor: Elastic-Scaling Framework for Distributed Streamin...

引用

16th IFIP WG 10.3 International conference on network and Parallel Computing, NPC 2019

作者： Mu, Weimin Jin, Zongze Wang, Junwei Zhu, Weilin Wang, Weiping Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030307080

In face of constant fluctuations and sudden bursts of data stream, elasticity of distributed stream processing system has become increasingly important. The proactive policy offers a powerful means to realize the effective elastic scaling. The existing methods lack the latent features of data stream, it leads the poor prediction. Furthermore, the poor prediction results in the high cost of adaptation and the instability. To address these issues, we propose the framework named BGElasor, which is a proactive and low-cost elastic-scaling framework based on the accurate prediction using deep neural networks. It can capture the potentially-complicated pattern to enhance the accuracy of prediction, reduce the cost of adaptation and avoid adaptation bumps. The experimental results show that BGElasor not only improves the prediction accuracy with three kinds of typical loads, but also ensure the end-to-end latency on QoS with low cost. © 2019, IFIP International Federation for Information processing.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

BRNN-GAN: Generative Adversarial networks with Bi-directional Recurrent neural networks for Multivariate Time Series Imputation 27

BRNN-GAN: Generative Adversarial Networks with Bi-directiona...

引用

27th IEEE International conference on Parallel and distributed Systems, ICPADS 2021

作者： Wu, Zejun Ma, Chao Shi, Xiaochuan Wu, Libing Zhang, Dian Tang, Yutian Stojmenovic, Milos Wuhan University China ShanghaiTech University China Singidunum University Serbia

ISBN: (纸本)9781665408783

Missing values appearing in multivariate time series often prevent further and in-depth analysis in real-world applications. To handle those missing values, advanced multivariate time series imputation methods are expected to (1) consider bi-directional temporal correlations, (2) model cross-variable correlations, and (3) approximate original data's distribution. However, most of existing approaches are not able to meet all the three above-mentioned requirements. Drawing on advances in machine learning, we propose BRNN-GAN, a generative adversarial network with bi-directional RNN cells. The BRNN cell is designed to model bi-directional temporal and cross-variable correlations, and the GAN architecture is employed to learn original data's distribution. By conducting comprehensive experiments on two public datasets, the experimental results show that our proposed BRNN-GAN outperforms all the baselines in terms of achieving the lowest Mean Absolute Error (MAE). © 2021 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Aerial Computing Offloading by distributed Deep Learning in Collaborative Satellite-terrestrial networks 13

Aerial Computing Offloading by Distributed Deep Learning in ...

引用

13th International conference on Wireless Communications and Signal processing, WCSP 2021

作者： Li, Haofei Chen, Chen Li, Cong Liu, Lei Gui, Guan Xidian University State Key Laboratory of Integrated Services Networks Xi'an China State Grid JiLin Province Electric Power Company Limited Information Communication Company Changchun China Nanjing University of Posts and Telecommunications College of Telecommunications and Information Engineering Nanjing China

ISBN: (纸本)9781665407854

With the rapid development of the Internet of Things (IoT) and its derivative technologies such as Aerial IoT (AIoT), the number of smart devices and their computing requirements have exploded. It makes it difficult for the existing ground base stations to guarantee the user's computing requirements and low latency requirements. The edge computing architecture of orbiting satellites, which provides feasible solutions to the above challenges. In this paper, we design a computing offloading strategy for users to minimize the weighted sum of latency and energy consumption in the cloud-edge-ground three layers hybrid AIoT architecture. Tasks can be calculated locally, on the satellite side, or forwarded to the cloud computing center. Then, the collaborative satellite-terrestrial network distributed offloading algorithm(CNDO) is proposed based on parallel neural networks to give multiple optimal offloading decisions in AIoT. Experimental results show that this scheme has a better performance compared with other comparison schemes. © 2021 IEEE.

关键词： computation offloading

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 << < 104 105 106 107 108 109 110 111 112 113 > >>

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：