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

8,198 篇 期刊文献
7,627 篇 会议
212 册 图书

馆藏范围

16,037 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

9,008 篇 工学
- 4,831 篇 计算机科学与技术...
- 3,741 篇 软件工程
- 1,561 篇 电子科学与技术（可...
- 1,510 篇 信息与通信工程
- 1,470 篇 电气工程
- 1,214 篇 控制科学与工程
- 869 篇 化学工程与技术
- 867 篇 生物工程
- 819 篇 材料科学与工程（可...
- 798 篇 光学工程
- 674 篇 生物医学工程（可授...
- 649 篇 机械工程
- 596 篇 仪器科学与技术
- 564 篇 动力工程及工程热...
- 436 篇 力学（可授工学、理...
- 348 篇 冶金工程
7,890 篇 理学
- 4,243 篇 物理学
- 3,029 篇 数学
- 1,072 篇 生物学
- 1,024 篇 统计学（可授理学、...
- 1,000 篇 化学
- 560 篇 系统科学
- 322 篇 地球物理学
1,862 篇 管理学
- 1,210 篇 管理科学与工程(可...
- 699 篇 图书情报与档案管...
- 616 篇 工商管理
737 篇 医学
- 599 篇 临床医学
- 496 篇 基础医学(可授医学...
- 291 篇 药学(可授医学、理...
324 篇 法学
- 277 篇 社会学
258 篇 经济学
195 篇 农学
183 篇 教育学
37 篇 文学
25 篇 艺术学
24 篇 军事学
4 篇 哲学
1 篇 历史学

主题

324 篇 deep learning
322 篇 computer science
245 篇 machine learning
195 篇 computational mo...
172 篇 accuracy
161 篇 optimization
151 篇 feature extracti...
149 篇 internet of thin...
133 篇 neural networks
131 篇 data mining
120 篇 predictive model...
119 篇 support vector m...
119 篇 artificial intel...
118 篇 computational in...
118 篇 real-time system...
117 篇 hadrons
106 篇 image segmentati...
100 篇 computer archite...
90 篇 educational inst...
86 篇 covid-19

机构

1,106 篇 cavendish labora...
1,038 篇 department of ph...
991 篇 physikalisches i...
989 篇 oliver lodge lab...
616 篇 fakultät physik ...
572 篇 department of ph...
567 篇 school of physic...
559 篇 horia hulubei na...
552 篇 iccub universita...
547 篇 school of physic...
535 篇 school of physic...
534 篇 h.h. wills physi...
532 篇 imperial college...
528 篇 nikhef national ...
524 篇 stfc rutherford ...
522 篇 university of ch...
510 篇 physik-institut ...
510 篇 infn laboratori ...
505 篇 school of physic...
504 篇 henryk niewodnic...

作者

284 篇 barter w.
266 篇 a. gomes
262 篇 beiter a.
253 篇 c. alexa
253 篇 c. amelung
251 篇 j. m. izen
251 篇 g. bella
251 篇 j. strandberg
251 篇 d. calvet
251 篇 bellee v.
248 篇 g. spigo
246 篇 blake t.
244 篇 f. siegert
244 篇 bowcock t.j.v.
243 篇 brundu d.
239 篇 s. chen
233 篇 betancourt c.
230 篇 y. tayalati
230 篇 borsato m.
227 篇 amato s.

语言

15,361 篇 英文
532 篇 其他
136 篇 中文
8 篇 日文
4 篇 德文
4 篇 法文
2 篇 朝鲜文
1 篇 俄文
1 篇 斯洛文尼亚文

检索条件"机构=Computer Science Applied Computer Technology"

共 16037 条记录，以下是451-460 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：

Fast whitespace correction with encoder-only transformers 61

Fast whitespace correction with encoder-only transformers

引用

61st Annual Meeting of the Association for Computational Linguistics, ACL-DEMO 2023

作者： Bast, Hannah Hertel, Matthias Walter, Sebastian University of Freiburg Department of Computer Science Freiburg Germany Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany

ISBN: (纸本)9781959429708

The goal of whitespace correction is to fix space errors in arbitrary given text. For example, given the text whi te space correctio nwithTransf or mers, produce whitespace correction with Transformers. We compare two Transformer-based models, a characterlevel encoder-decoder model and a byte-level encoder-only model. We find that the encoderonly model is both faster and achieves higher quality. We provide an easy-To-use tool that is over 900 times faster than the previous best tool, with the same high quality. Our tool repairs text at a rate of over 200 kB/s on GPU, with a sequence-Averaged F1-score ranging from 87.5% for hard-To-correct text up to 99% for text without any spaces. © ACL-DEMO 2023. All rights reserved.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

On Batching Variable Size Inputs for Training End-to-End Speech Enhancement Systems 48

On Batching Variable Size Inputs for Training End-to-End Spe...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Gonzalez, Philippe Sonne Alstrom, Tommy May, Tobias Technical University of Denmark Department of Health Technology Denmark Technical University of Denmark Department of Applied Mathematics and Computer Science Denmark

ISBN: (纸本)9781728163277

The performance of neural network-based speech enhancement systems is primarily influenced by the model architecture, whereas training times and computational resource utilization are primarily affected by training parameters such as the batch size. Since noisy and reverberant speech mixtures can have different duration, a batching strategy is required to handle variable size inputs during training, in particular for state-of-the-art end-to-end systems. Such strategies usually strive for a compromise between zero-padding and data randomization, and can be combined with a dynamic batch size for a more consistent amount of data in each batch. However, the effect of these strategies on resource utilization and more importantly network performance is not well documented. This paper systematically investigates the effect of different batching strategies and batch sizes on the training statistics and speech enhancement performance of a Conv-TasNet, evaluated in both matched and mismatched conditions. We find that using a small batch size during training improves performance in both conditions for all batching strategies. Moreover, using sorted or bucket batching with a dynamic batch size allows for reduced training time and GPU memory usage while achieving similar performance compared to random batching with a fixed batch size. © 2023 IEEE.

关键词： Speech enhancement

来源：评论

学校读者我要写书评

暂无评论

Analyzing video footage from security cameras using the Amped FIVE professional tool specifically for the identification of vehicle license plates 4

Analyzing video footage from security cameras using the Ampe...

引用

4th International Conference on Computing, Networking, Telecommunications and Engineering sciences Applications, CoNTESA 2023

作者： Gvozdanovic, Misel Delija, Damir Tulicic, Domagoj Sirovatka, Goran Zagar, Marinko Bilic, Krunoslav Zagreb University of Applied Science Department of Informatics and Computing Zagreb Croatia University of Applied Sciences in Information Technology Department of Computer Systems and Networks Zagreb Croatia

ISBN: (纸本)9798350382754

This paper describes problems of improving security cameras' video footage for forensic investigation. When processing records, one encounters problems with low resolution, poor lighting, or excessive distance of a key object in an image or video. Using the Amped FIVE Professional tool, forensic scientists create videos and analyze and process the record itself using various filters. Record quality demands a choice of video filters. The use and selection of filters show the improvement of the record itself to the level to which useful information can be obtained in this case of vehicle license plates. The presented roadmap can be used as the base for further video forensic research. © 2023 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Blockchain based Secure Erlang Server for Request based Group Communication over XMPP

Blockchain based Secure Erlang Server for Request based Grou...

引用

2023 International Conference on Advances in Intelligent Computing and Applications, AICAPS 2023

作者： Johnpaul, C.I. Vivekanandan, Manojkumar Premkamal, Praveen Kumar Ramya, R. St. Thomas College Department of Computer Science and Applications Kerala Thrissur India Srm University-AP School of Engineering and Applied Sciences Department of Computer Science and Engineering Andhra Pradesh Amaravati India Kamaraj College of Engineering and Technology Department of Computer Science and Engineering Virudhunagar India

ISBN: (纸本)9798350333817

Many real world activities in computer science scenarios are linked with concurrency and security related issues and have to handle large number of processes to be executed in parallel with false safe security solutions. There are many traditional methods in programming languages to handle concurrency. Concurrency is one of the major issues that need to be addressed by most of the servers when dealing with the group communication operations. Security of the data as well as the credibility of the users are the other aspects when a group of users involve in real-time communication. Many light-weighted servers are designed to carryout elementary operations of request handling, file sharing etc. In design of such servers having large number of clients, the request service handling will be based on the individual server programs. Keeping track of individual credibility and establishing concurrency solutions in server design is challenging. The whole work describes the significance and implementation of an Erlang based XMPP server in comparison with a Python based XMPP server with a view to service the client request handling operations for sending messages, group chatting, buddy-list creation, presence identification integrated with XML messaging pattern as per the XMPP protocol. We also accomplish the security and credibility of the users using a blockchain based interface that keep track of user activities during group communication. The security analysis is also performed for blockchain based interface. © 2023 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

A Novel Federated Learning Framework for Healthcare Applications Using Wearable Devices 4

A Novel Federated Learning Framework for Healthcare Applicat...

引用

4th IEEE International Conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Natarajan, Rajesh Krishna, Sujatha Ranjith, Christodoss Prasanna University of Technology and Applied Sciences Al-Aqr 324 College of Computing and Information Sciences Information Technology Department Shinas Oman Messiah University Computer Science Department MechanicsburgPA United States

ISBN: (纸本)9798331518882

A key necessity in managing signals for processing and generating useful information in the healthcare domain is the use of many algorithms. Traditional computing methods have been successful but may not be effective in the future as secure privacy matters. This has led to the increasing popularity of machine learning technologies. However, we present a novel device for devices and sensors for federated learning (FL), which is aimed at establishing a new, safer framework. This pattern uses machine learning with a lot of emphasis on the availability of the devices. In such a case, models for the detection, monitoring, and management of diseases can be created. The FL approach is also believed to be applicable to several healthcare contexts. © 2025 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Leveraging Internet of Things (IoT) Sensors and Deep Learning Techniques for Precision Agriculture 1

Leveraging Internet of Things (IoT) Sensors and Deep Learnin...

引用

1st International Conference on Innovative Engineering sciences and Technological Research, ICIESTR 2024

作者： Wilfred Blessing, N.R. Pyingkodi, M. Wasim Haidar, S.K. Palarimath, Suresh Paravathavarthini, S. Balakumar, C. Sheeja Kumari, V. Sutherlin Subitha, G. Seldev Christopher, S. University of Technology and Applied Sciences-Ibri College of Computing and Information Sciences Ibri Oman Kongu Engineering College Department of Computer Applications Erode India University of Technology and Applied Sciences-Salalah College of Computing and Information Sciences Salalah Oman Kongu Engineering College Department of Computer Technology Erode India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India Saveetha Institute of Medical and Technical Sciences Department of Computational Intelligence Chennai India Stella Mary's College of Engineering Department of Computer Science and Engineering Aruthenganvilai India St. Xavier's Catholic College of Engineering Department of Computer Science and Engineering Nagercoil India

ISBN: (纸本)9798350348637

Precision agriculture, driven by advancements in technology, aims to optimize farming practices by utilizing data and technology to enhance efficiency, productivity, and sustainability This research introduces an innovative pilot investigation centered on the convergence of two revolutionary technologies are the Internet of Things (IoT) and Deep Learning. With a specific focus on advancing precision agriculture, the primary objective of this study is to evaluate the combined effects of data collection facilitated by IoT and analytical capabilities of deep learning in enhancing and optimizing various agricultural processes. The integration of IoT in agriculture has revolutionized data acquisition, employing an array of sensors to monitor critical parameters such as soil moisture, temperature, and crop health. Concurrently, Deep Learning, a subset of artificial intelligence, exhibits the potential to glean actionable insights from voluminous datasets, offering advanced analytics and predictive capabilities. This study investigates the practical implementation and efficacy of this integration in a controlled agricultural setting. Sensors strategically positioned in the pilot study capture real-time data, while deep learning algorithms process and analyze this information. The primary objectives include evaluating the effectiveness of this combined technology in optimizing irrigation schedules, predicting crop yields, and identifying anomalies in crop health. Preliminary findings underscore the transformative potential of IoT and Deep Learning, empowering farmers with real-time data for informed decision-making. Key considerations encompassed in the study include IoT Sensors, Deep learning algorithms, and user adoption. The research not only sheds light on the technical intricacies of the integration but also delves into the challenges and opportunities inherent in merging these technologies within the agricultural landscape. As agriculture transitions towards the next

关键词： Smart agriculture

来源：评论

学校读者我要写书评

暂无评论

ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles 15

ZeitGeist: A Generic Tool Supporting the Dissemination of Ti...

引用

15th International Conference on Knowledge Management and Information Systems, KMIS 2023 as part of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023

作者： Schmidt, Andreas Koubaa, Mohamad Anis Schweikert, Jan Stucky, Karl-Uwe Süß, Wolfgang Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Department of Computer Science and Business Information Systems University of Applied Sciences Karlsruhe Germany

ISBN: (纸本)9789897586712

An important point for the widespread dissemination of FAIR-data is the lowest possible entry barrier for preparing and providing data to other scientists according to the FAIR criteria. If scientists have to manually extract, transform and annotate the data according to the FAIR criteria and then export it to make it available to the public, this requires a significant investment of time that does not primarily reward the scientist who prepares and provides the data. The Energy Lab at KIT is running a large cluster of an Influx database management system with energy related time series data being stored in a variety of individual databases over periods of up to 15 years. In order to increase the willingness to make data available to the scientific public, we develop a tool that greatly supports and automates the publication and annotation process of time series data stored in Influx databases. Copyright © 2023 by SCITEPRESS - science and technology Publications, Lda.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

Enhanced accuracy of deep learning method for fruit images classification 25

Enhanced accuracy of deep learning method for fruit images c...

引用

25th International Arab Conference on Information technology, ACIT 2024

作者： Arabiat, Mohammad Abuowaida, Suhaila Alshdaifat, Nawaf Aburomman, Ahmad Al Henawi, Esraa Dmour, Mohmmad Elrashidi, Ali Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Al al-Bayt University Faculty of Information Technology Department of Computer Science Mafraq Jordan Applied Science Private University Faculty of Information Technology Amman Jordan Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

In the last few years, artificial intelligence has shown its importance and ability in computer vision due to its high level of accuracy and wide acceptance. The main goal of the research is to look into a better way to separate different types of fruits. Although deep learning is used, the standard classification methods for different types of fruit don't work very well. The main steps of the recommended better multiple fruit classification method are: 1) Making changes to the filter's size. Selecting the most suitable number of repeats is part of the process of improving the ResNet-101 block. 3) It is proposed that there be one more convolutional layer. Exists support for the suggested method after collecting and labeling 27,000 pictures as part of an actual study. The dataset with many fruits is split into two parts: 80% is used for training and 20% is used for testing. These pictures were used to train an application based on deep learning (DL) to help successfully determine multiple fruit objects in images. Then and then possible to compare the results of this method to the most current methods in the area of object division. The application being studied at does better than expected in terms of accuracy AP in a range of levels. The values always go farther than the equivalent measures of three widely used methods. Compared to the other methods, the suggested one takes less time to train. There are higher numbers for the thresholds than there are for the state of the art method's thresholds © 2024 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Incremental Learning Strategy with Multi-dimensional Knowledge Distillation for One-stage Object Detection 22

Incremental Learning Strategy with Multi-dimensional Knowled...

引用

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Li, Yimeng Liu, Xuejiao Xiang, Xueshuang Tan, Yu-An Meng, Weizhi School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark

ISBN: (纸本)9798331527471

In practical applications, object detectors often encounter unknown classes samples. As object detection datasets undergo continuous development, the need arises for object detectors to adeptly recognize an escalating array of new classes while retaining the original detection capability. This paper introduces a new class incremental object detection learning framework with multi-dimensional knowledge distillation, using Yolov5 as the foundational detection model. Specifically, we utilize local feature distillation, attention distillation and global feature distillation to preserve information in the original model’s feature maps. Additionally, we employ response distillation to ensure the model remains responsive to previous classes. In comparison to the state-of-the-art methods, our approach achieves higher overall accuracy on PASCAL VOC 2007. Especially in the "19+1" incremental task, our approach gets the highest mAP@0.5 of 0.697 with a minimum mean AP decline rate of 4.45%. For the "4+3" and "6+1" tasks on KITTI, our approach preserves the model’s responsiveness to the original task more effectively while achieving the highest overall accuracy. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Multi Label Classification Algorithm Based on Conditional Local Correlations among Labels and Ensemble Learning 25

Multi Label Classification Algorithm Based on Conditional Lo...

引用

25th International Arab Conference on Information technology, ACIT 2024

作者： Alazaidah, Raed Nasir, Ola Hadi, Wael Samara, Ghassan Al Daoud, Essam Aljaidi, Mohammad Khouj, Mohammed Talat Elsoud, Esraa Abu Alzoubi, Haneen Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Petra University Faculty of Information Technology Department of Cyber Security Amman Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Applied Science Private University Faculty of Information Technology Department of Computer Science Amman Jordan

ISBN: (纸本)9798331540012

Multi-Label Classification (MLC) is an advanced form of traditional classification, where each data instance is simultaneously associated with multiple labels. The importance of MLC has increased significantly in recent years, due to its wide range of application areas. Modern algorithms, when faced with the challenge of multiple labels, continue to show suboptimal performance, conversely, they show significantly superior performance when processing single-label datasets. This paper proposes a new algorithm to deal with the problem of transforming datasets from multiple labels to single labels by exploiting conditional and local correlations between labels after applying the Apriori predictive algorithm to extract relationships. Six ensemble learning models: Voting Hard, Voting Soft, Voting Weighted, Stacking LR, Stacking RF, and Stacking SVM, along with four classification models: SMO, DecisionStump, Random Forest, and Random Committee, were applied to three datasets. The algorithm showed effective and good performance by comparing the results of the proposed Multi Label Classification algorithm based on Conditional Local Correlations among Labels (MLC-CLCL) with several popular algorithms for dealing with multiple labels. © 2024 IEEE.

关键词： Contrastive Learning

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 << < 42 43 44 45 46 47 48 49 50 51 > >>

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：