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

332 篇 会议
34 篇 期刊文献

馆藏范围

366 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

242 篇 工学
- 194 篇 计算机科学与技术...
- 169 篇 软件工程
- 71 篇 信息与通信工程
- 56 篇 控制科学与工程
- 55 篇 电子科学与技术（可...
- 44 篇 电气工程
- 21 篇 生物工程
- 20 篇 生物医学工程（可授...
- 17 篇 光学工程
- 16 篇 机械工程
- 15 篇 化学工程与技术
- 12 篇 力学（可授工学、理...
- 12 篇 土木工程
- 11 篇 建筑学
- 10 篇 仪器科学与技术
- 9 篇 航空宇航科学与技...
- 8 篇 材料科学与工程（可...
163 篇 理学
- 116 篇 数学
- 58 篇 物理学
- 25 篇 统计学（可授理学、...
- 21 篇 生物学
- 17 篇 化学
68 篇 管理学
- 43 篇 管理科学与工程(可...
- 37 篇 工商管理
- 34 篇 图书情报与档案管...
26 篇 教育学
- 26 篇 教育学
13 篇 法学
- 9 篇 社会学
12 篇 经济学
- 12 篇 应用经济学
10 篇 医学
- 9 篇 临床医学
- 8 篇 基础医学(可授医学...
3 篇 农学
2 篇 军事学

主题

37 篇 computer science
12 篇 neural networks
12 篇 engineering educ...
10 篇 computational mo...
9 篇 feature extracti...
9 篇 australia
9 篇 training
8 篇 application soft...
7 篇 control systems
7 篇 testing
6 篇 learning systems
6 篇 neurons
6 篇 computer archite...
6 篇 data mining
6 篇 monitoring
6 篇 image coding
6 篇 distributed comp...
5 篇 electroencephalo...
5 篇 internet
5 篇 costs

机构

6 篇 sch. of elec. en...
5 篇 sch. of electr. ...
5 篇 school of electr...
4 篇 department of co...
4 篇 sch. of electr. ...
4 篇 sch. of comp. sc...
4 篇 sch. of info. te...
3 篇 department of co...
3 篇 department of en...
3 篇 sch. of comp. sc...
3 篇 sch. of eng. and...
3 篇 department of co...
3 篇 school of comput...
3 篇 sch. of comput. ...
3 篇 sch. of comput. ...
3 篇 sch. of electron...
3 篇 baylor universit...
3 篇 school of comput...
3 篇 school of electr...
3 篇 sch. of elec. en...

作者

4 篇 tong zhang
4 篇 assaf mansour h.
4 篇 sul seung-ki
4 篇 petriu emil m.
4 篇 sahinoglu mehmet
4 篇 das sunil r.
3 篇 van treuren ken
3 篇 santoro nicola
3 篇 jin chuan
3 篇 jin liwu
3 篇 park hee-joon
3 篇 shu yantai
3 篇 cho jin-ho
3 篇 park il-yong
3 篇 lee jeong-woo
3 篇 flocchini paola
3 篇 yang oliver w.w.
3 篇 georgiopoulos mi...
2 篇 fung chun che
2 篇 xue jia

语言

360 篇 英文
5 篇 其他
1 篇 日文

检索条件"机构=Sch. of Computer Science and Engineering"

共 366 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：

Efficient 3D Transformer with cluster-based Domain-Adversarial Learning for 3D Medical Image Segmentation

Efficient 3D Transformer with cluster-based Domain-Adversari...

引用

IEEE International Symposium on Biomedical Imaging

作者： Haoran Zhang Hao Chen Sch. of Artificial Intelligence and Automation Huazhong University of Science and Technology Dept. of Computer Science and Engineering The Hong Kong University of Science and Technology Dept. of Chemical and Biological Engineering The Hong Kong University of Science and Technology

Real-world application of volumetric medical image segmentation is still challenging due to the domain shift problem and the disability to process volumetric information efficiently by existing algorithms. To address these problems, we propose a 3D Swin Transformer with a pyramidal downsampling strategy to process volumetric information efficiently, dubbed as PDSwin. Specifically, the improved 3D Swin Transformer includes a spatial downsampling strategy that downsamples 2D slices pyramidally according to the spatial relationship, reducing the computation complexity while providing a wider downsampled receptive field. Furthermore, we propose a cluster-based domain-adversarial learning algorithm to attenuate the domain shift problem. The algorithm generates fine-grained cluster-based domains instead of employing center-based domains, ameliorating the domain-adversarial learning performance. We evaluated our model against other competitive models on brain stroke lesion segmentation and prostate segmentation tasks. Extensive experimental results indicated that our proposed model outperforms other models, demonstrating the efficacy of our proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Low Voltage CMOS Class AB Current Mirror/Precision Rectifier

Low Voltage CMOS Class AB Current Mirror/Precision Rectifier

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Anindita Paul Jaime Ramirez-Angulo Manaswini Gangineni Jesus Huerta-Chua Department of Computer Science & Electronics Morehead State University Morehead USA Electronic Engineering Department Instituto Technologico Superior de Poza Rica Poza Rica Mexico Klipsch Sch. Of Elect. & Computer Engineering NMSU Las Cruces USA

A low-voltage CMOS class AB current mirror/precision rectifier is introduced that can handle positive and negative current signals much larger than the bias current. It is based on a current switch and two current mirrors. Simulations in 180nm CMOS technology with a 1v supply and a 1μA bias current show that the circuit can handle 200μA peak-to-peak bidirectional current signals with high accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Performance Assessment of an Extremely Energy-Efficient Binary Neural Network Using Adiabatic Superconductor Devices

Performance Assessment of an Extremely Energy-Efficient Bina...

引用

IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)

作者： Olivia Chen Zhengang Li Tomoharu Yamauchi Yanzhi Wang Nobuyuki Yoshikawa Dept. Computer Science Tokyo City University Tokyo Japan Dept. Electrical and Computer Engineering Northeasetern University Boston USA Grad. Sch. Informative Engineering Tokyo City University Tokyo Japan Dept. Electrical and Computer Engineering Yokohama National University Yokohama Japan

Binary Neural Networks (BNNs) are gaining popularity for solving real-world problems using Deep Neural Networks (DNNs), such as image recognition and natural language processing. BNNs use binary precision for weights and activations, reducing memory usage by 32 times compared to conventional networks using 32-bit floating-point precision. Among various types of BNNs, AQFP-based BNNs utilizing superconducting logic families are promising for energy-efficient computing, using magnetic flux quantization and quantum interference in Josephson-junction-based superconductor loops. This paper presents a performance assessment of a novel AQFP-based BNN architecture, highlighting scalability issues caused by increased inductance in the analog accumulation circuit. We also discuss potential optimization approaches to address these issues and improve scalability.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploration of TPU Architectures for the Optimized Transformer in Drainage Crossing Detection

Exploration of TPU Architectures for the Optimized Transform...

引用

IEEE International Conference on Big Data

作者： Amirhossein Nazeri Denys W. Godwin Aikaterini Maria Panteleaki Iraklis Anagnostopoulos Michael I. Edidem Ruopu Li Tong Shu Dept. of Automotive Engineering Clemson University Clemson SC USA Graduate School of Geography Clark University Worcester MA USA Sch. of Electr. Comp. and Biomed. Engr. Southern Illinois University Carbondale IL USA Sch. of Earth Systems and Sustain. Southern Illinois University Carbondale IL USA Dept. of Computer Science and Engr. University of North Texas Denton TX USA Department of Computer Science and Engineering University of North Texas Denton TX USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Understanding hydrologic connectivity within landscapes is crucial for managing environmental challenges. Despite advancements in high-resolution Digital Elevation Models (DEMs) derived from Light Detection and Ranging (LiDAR) technology, accurately delineating hydrologic connectivity remains challenging due to disruptions caused by virtual flow barriers, such as roads and bridges. This study addresses this issue by enhancing the detection performance and reducing the latency of Transformer models for image detection of drainage crossings. We retrained a Detection Transformer (DETR) with a specialized recipe to improve culvert detection performance. Owing to the high susceptibility of LiDAR-based DEMs to measurement noise and varying data modalities, we conducted extensive data preprocessing to ensure DETR compatibility with the culvert dataset. Ablation studies on input size indicate that the model performs optimally with 800×800 pixel inputs, demonstrating its adaptability to new data modalities. Additionally, we employed Tensor Processing Units (TPUs) to decrease the model’s latency. We developed a novel strategy to optimize TPU architecture, utilizing genetic algorithms to expedite the discovery of optimal TPU configurations for detection deployment. Our model surpasses the performance of previous models on the same task. This work not only addresses the computational complexities of deploying advanced object detection in environmental contexts but also significantly contributes to the precise and efficient monitoring of hydrologic connectivity.

关键词： Training Adaptation models Computational modeling Transfer learning computer architecture Watersheds Object detection Transformers Data models Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Cross-Subject EEG Emotion Recognition Using Domain Adaptive Few-Shot Learning Networks

Cross-Subject EEG Emotion Recognition Using Domain Adaptive ...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Run Ning C.L. Philip Chen Tong Zhang Sch. of Computer Science&Engineering South China University of Technology Guangzhou China Sch. of Computer Science&Engineering South China University of Technology Pazhou Lab Guangzhou China

ISBN: (纸本)9781665429825

Due to the individual differences and nonstationary of EEG signals, it is difficult to classify EEG emotions with traditional machine methods, which assume that the training and testing set come from the same data distribution, but this assumption is usually not true in the EEG field, therefore the accuracy of emotion recognition is very poor. In this paper, a Single-Source Domain Adaptive Few-Shot Learning Networks (SDA-FSL) was proposed for cross-subject EEG emotion recognition. This is the first time that domain adaptation method with few-shot learning has been used in the field of EEG emotion recognition. A CBAM-based feature mapping module was designed to extract the common features of the two domains, and the domain adaptation module was used to align the data distribution of two domains. In addition, Prototypical Networks with instance-attention mechanism is introduced to preserve domain-specific information. The proposed method was evaluated on DEAP and SEED datasets in within-dataset and cross-dataset experiments under various N-way k-shot settings. Experimental results show that the performance of SDA-FSL outperforms other comparison methods and has superior generalization performance on cross-dataset experiments.

关键词： Training Electrodes Emotion recognition Adaptive systems Conferences Feature extraction Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Joint Participation Incentive and Network Pricing Design for Federated Learning 42

Joint Participation Incentive and Network Pricing Design for...

引用

42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Ding, Ningning Gao, Lin Huang, Jianwei Northwestern University Department of Electrical and Computer Engineering EvanstonIL60208 United States Shenzhen Research Institute of Big Data Shenzhen518172 China Harbin Institute of Technology Sch. of Electronics and Info. Eng. and the Guangdong Prov. Key Lab. of Aerosp. Commun. and Networking Technol. Shenzhen China The Chinese University of Hong Kong Shenzhen School of Science and Engineering Shenzhen Research Institute of Big Data Shenzhen518172 China

ISBN: (纸本)9798350334142

Federated learning protects users' data privacy though sharing users' local model parameters (instead of raw data) with a server. However, when massive users train a large machine learning model through federated learning, the dynamically varying and often heavy communication overhead can put significant pressure on the network operator. The operator may choose to dynamically change the network prices in response, which will eventually affect the payoffs of the server and users. This paper considers the under-explored yet important issue of the joint design of participation incentives (for encouraging users' contribution to federated learning) and network pricing (for managing network resources). Due to heterogeneous users' private information and multi-dimensional decisions, the optimization problems in Stage I of multi-stage games are non-convex. Nevertheless, we are able to analytically derive the corresponding optimal contract and pricing mechanism through proper transformations of constraints, variables, and functions, under both vertical and horizontal interaction structures of the participants. We show that the vertical structure is better than the horizontal one, as it avoids the interests misalignment between the server and the network operator. Numerical results based on real-world datasets show that our proposed mechanisms decrease server's cost by up to 24.87% comparing with the state-of-the-art benchmarks. © 2023 IEEE.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a Memory Protection Mechanism Adhering to the Specifications of AUTOSAR OS SC3

Design and Implementation of a Memory Protection Mechanism A...

引用

Communication, Image and Signal Processing (CCISP), International Conference on

作者： Zhiwei Miao Shuanghao Xu Jianpei Liu Zhiguo Wang Bin Wen Sch. of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China Product Development Department Beijing Siener Electronics Tech. Development Co. Ltd. Beijing China

As the dynamics of intelligentization, connectivity, electrification, and collaborative processes within the automotive sector persist in their rapid evolution, there has been an escalating focus on the matter of functional safety within vehicular operating systems. Within the context of this evolving landscape, the present sch.larly work offers an exposition on the conception and realization of a memory protection mechanism in adherence to the AUTOSAR OS SC3 standard. In response to the limitations inherent in traditional memory protection mechanisms, necessitating manual configuration of address ranges for the determination of protection intervals, this novel mechanism introduces an approach for the dynamic acquisition of addresses and the establishment of protection range parameters. The practical execution and empirical assessment of this mechanism transpired on the Infineon AURIX TC275 microcontroller. The outcomes of the testing procedures elucidate that this approach not only fulfills the requisites of memory protection but also augments code portability and development efficiency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

BCNN: A Bantamweight Convolutional Neural Network for P300 Detection

BCNN: A Bantamweight Convolutional Neural Network for P300 D...

引用

IEEE Signal Processing in Medicine and Biology Symposium (SPMB)

作者： M. Liu S. Wang F. R. Beyette School of Electrical and Computer Engineering University of Georgia Athens Georgia USA Sch. of Math. and Info. Sci. & Tech Hebei Normal Univ. of Sci. & Tech Qinhuangdao Hebei China School of Information Science and Engineering Yanshan University Qinhuangdao Hebei China

As one kind of Event-Related Potentials (ERPs), P300 plays an important role in studying neural activities and cognitive processes, and lays the foundation for P300 speller – the Brain computer Interface (BCI) working by detecting P300. However, due to P300’s high subject variability and low Signal Noise Ratio (SNR), it’s always a challenge to do P300 detection. Convolutional Neural Networks (CNNs) have been widely recognized as effective methods for P300 detection, leading to the development of increasingly complex CNN architectures for P300 detection in recent years. However, this paper takes a different approach by proposing the bantamweight CNN (BCNN), the simplest and fast-training CNN for P300 detection. BCNN comprises only one convolutional filter and a total of 141 parameters. Surprisingly, it achieves state-of-the-art performance after just 2 epochs of training, making it an exceptionally lightweight and fast CNN for P300 detection. BCNN not only provides new ideas for CNN design, but also effectively address resource and time constrained situations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cognitive-inspired Post-processing of optical character recognition for Swedish addresses 21

Cognitive-inspired Post-processing of optical character reco...

引用

21st IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2022

作者： Andersson, Moa Kanwal, Summrina Khan, Faiza School of Electrical Engineering and Computer Science Kth Royal Institute of Technology in Stockholm Sweden Sch. of Elec. Eng. and Comp. Sci. Kth Roy. Inst. of Technol. in Stockholm Ctr. for Appl. Intelligent Syst. Res. Halmstad Univ. Sweden Riphah International University Faculty of Computing Islamabad Pakistan

ISBN: (纸本)9781665490849

Optical character recognition (OCR) has many ap-plications, such as digitizing historical documents, automating processes, and helping visually impaired people read. However, extracting text from images into a digital format is not an easy problem to solve, and the outputs from the OCR frameworks often include errors. The complexity comes from the many variations in (digital) fonts, handwriting, lighting, etc. To tackle this problem, this thesis investigates two different methods for correcting the errors in OCR output. The used dataset consists of Swedish addresses. The methods are therefore applied to postal automation to investigate the usage of these methods for further automating postal work by automatically reading addresses on parcels using OCR. The first method, the lexical implementation, uses a dataset of Swedish addresses so that any valid address should be in this dataset (hence there is a known and limited vocabulary), and misspelled addresses are corrected to the address in the lexicon with the smallest Levenshtein distance. The second approach uses the same dataset, but with artificial errors, or artificial noise, added. The addresses with this artificial noise are then used together with their correct spelling to train a machine learning model based on Neural machine translation (NMT) to automatically correct errors in OCR read addresses. The results from this study could contribute by defining in what direction future work connected to OCR and postal addresses should go. The results were that the lexical implementation outperformed the NMT model. However, more experiments including real data would be required to draw definitive conclusions as to how the methods would work in real-life applications. © 2022 IEEE.

关键词： Optical character recognition

来源：评论

学校读者我要写书评

暂无评论

Multi-Channel EEG Based Emotion Recognition Using Temporal Convolutional Network and Broad Learning System

Multi-Channel EEG Based Emotion Recognition Using Temporal C...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Xue Jia Tong Zhang C. L. Philip Chen Zhulin Liu Long Chen Guihua Wen Bin Hu Sch. of Computer Science&Engineering South China University of Technology Guangzhou China Science University of Macau Macau China Sch. of Information Science&Engineering Lanzhou University Lanzhou China

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

Automatic real-time emotion recognition based on multi-channel EEG signals is a significant and challenging task in neurology and psychiatry. In recent years, deep learning has been used in EEG emotion recognition. However, many existing deep learning based methods still require complex pre-processing or additional feature extraction, which make it difficult to achieve real-time emotion recognition. In this paper, an end-to-end model named Temporal Convolutional Broad Learning System (TCBLS) was designed for multi-channel EEG based emotion recognition. The TCBLS takes one-dimensional EEG signals as input, then extracts emotion-related features of EEG automatically. In this model, the Temporal Convolutional Network (TCN) is designed to extract EEG temporal features and deep abstract features simultaneously, then Broad Learning System (BLS) is used to map the features to a more discriminative space and further enhance the features. We evaluated our method on DEAP database, performing 10-fold cross-validation on each subject to obtain the classification accuracy. Experimental results indicate that the performance of TCBLS is better than other comparison methods, and the mean accuracy of TCBLS is 99.5755% and 99.5781% on valence and arousal classification task respectively. The results demonstrate the effectiveness and robustness of TCBLS in EEG emotion recognition.

关键词： Learning systems Emotion recognition Convolution Feature extraction Brain modeling Electroencephalography Task analysis

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37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：