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

30,639 篇 会议
4,718 篇 期刊文献
247 册 图书

馆藏范围

35,604 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

22,147 篇 工学
- 16,114 篇 计算机科学与技术...
- 13,553 篇 软件工程
- 5,862 篇 信息与通信工程
- 3,503 篇 控制科学与工程
- 2,697 篇 电子科学与技术（可...
- 2,656 篇 电气工程
- 2,355 篇 生物工程
- 1,885 篇 生物医学工程（可授...
- 1,526 篇 光学工程
- 1,365 篇 机械工程
- 1,226 篇 动力工程及工程热...
- 1,201 篇 仪器科学与技术
- 1,025 篇 化学工程与技术
- 861 篇 安全科学与工程
- 724 篇 交通运输工程
11,321 篇 理学
- 6,196 篇 数学
- 3,046 篇 物理学
- 2,578 篇 生物学
- 2,039 篇 统计学（可授理学、...
- 1,358 篇 系统科学
- 1,092 篇 化学
5,764 篇 管理学
- 3,362 篇 管理科学与工程(可...
- 2,686 篇 图书情报与档案管...
- 1,871 篇 工商管理
1,585 篇 医学
- 1,377 篇 临床医学
- 1,286 篇 基础医学(可授医学...
- 851 篇 药学(可授医学、理...
- 664 篇 公共卫生与预防医...
1,060 篇 法学
- 856 篇 社会学
670 篇 经济学
- 670 篇 应用经济学
485 篇 农学
443 篇 教育学
161 篇 文学
78 篇 军事学
40 篇 艺术学
1 篇 哲学

主题

1,057 篇 accuracy
839 篇 feature extracti...
824 篇 computational mo...
700 篇 deep learning
692 篇 training
686 篇 computer science
525 篇 machine learning
518 篇 real-time system...
507 篇 support vector m...
441 篇 predictive model...
417 篇 internet of thin...
351 篇 computer archite...
348 篇 data models
339 篇 convolutional ne...
325 篇 reliability
310 篇 optimization
300 篇 data mining
279 篇 routing
259 篇 wireless sensor ...
255 篇 artificial intel...

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
76 篇 tno technical sc...
66 篇 università di ca...
65 篇 université de st...
63 篇 dept. of informa...
61 篇 nikhef national ...
59 篇 dept. of compute...
58 篇 dept. of informa...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
49 篇 dept. of compute...
49 篇 dept. of compute...
44 篇 dept. of electri...
43 篇 university würzb...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
82 篇 kalekin o.
81 篇 chen a.
78 篇 díaz a.f.
78 篇 boumaaza j.
77 篇 coleiro a.
76 篇 gozzini s.r.
72 篇 dallier r.
69 篇 huang f.
64 篇 anguita m.
52 篇 kulikovskiy v.
43 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

34,349 篇 英文
833 篇 其他
312 篇 中文
57 篇 日文
51 篇 朝鲜文
2 篇 德文
1 篇 法文
1 篇 葡萄牙文
1 篇 斯洛文尼亚文

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

共 35604 条记录，以下是131-140 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：

An Intelligent Forecasting Classification Model for Traffic Analysis using Machine Learning Techniques 4

An Intelligent Forecasting Classification Model for Traffic ...

引用

4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Kishor, Bodla Tiwari, Rajesh Patra, Raj Kumar Pinjakar, Latika Singh, Mahesh Cmr Engineering College Dept. of Computer Science and Engineering Hyderabad India Cmr Technical Campus Dept. of Computer Science and Engineering Hyderabad India Symbiosis Institute of Technology Dept. of Computer Science and Engineering Nagpur India Shri Shankaracharya Technical Campus Dept. of Eee Durg Bhilai India

ISBN: (纸本)9798350343670

In addition to taking care of the normal citizens, Road Traffic protection is also one of the main issue for corporations governing the transportation. We use data mining techniques to get the hidden matter from the database. The applications of Data mining is there in various fields such as fraud detection, marketing and many more. Many countries were affected due to many decisions that were taken by the governments one such issue is globalization. This has brought some drastically changes in the intake level and the financial related activities and this has given a boost to transportation department. Understanding the importance of the street protection the authorities are putting effort to know the reasons behind the street accidents. The increase in the street injuries made it difficult to determine the limitations of the street injuries. This paper explains the street injuries frequency from analysing the database. This work is about 95% efficient. © 2024 IEEE.

关键词： classification data mining machine learning traffic analysis Transportation models

来源：评论

学校读者我要写书评

暂无评论

Disease Detection And Severity Prediction Of Pomegranate Fruit 15

Disease Detection And Severity Prediction Of Pomegranate Fru...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Paul, Poulin Manishankar, S. Satheesh Kumar, R. Sahrdaya College of Engineering and Technology Dept. of Computer Science and Engineering Kerala Thrissur India Jawaharlal College of Engineering and Technology Dept. of Computer Science and Engineering Kerala Palakkad India

ISBN: (纸本)9798350370249

This paper presents an integrated framework for the comprehensive analysis of diseases affecting pomegranate fruit. The suggested system, which makes use of deep learning techniques, includes semantic segmentation for diseased region localization, multiclass illness classification, and image processing-based severity assessment. Initially, four common diseases - Alternaria, Anthracnose, Bacterial Blight, and Cer-cospora - are successfully identified through the use of a Convolutional Neural Network (CNN) for multiclass classification. Then, annotated photos are used as training data for Semantic Segmentation, which uses the UNet architecture to identify the unhealthy spots within the fruit. The area and percentage of the segmented region are determined, and thresholds for high, medium, and low severity levels are then defined. The segmentation results are then used as inputs for severity estimate. Early identification and intervention tactics are made easier by the severity level prediction, which is based on the proportion of the segmented region. In order to improve pomegranate fruit management methods, the suggested framework provides a thorough method of disease analysis by combining categorization, semantic segmentation, and severity prediction. © 2024 IEEE.

关键词： Annotation Convolutional Neural Networks Deep learning Semantic segmentation Unet

来源：评论

学校读者我要写书评

暂无评论

A Recent Survey on Bone Cancer Detection using Deep Learning Techniques 2

A Recent Survey on Bone Cancer Detection using Deep Learning...

引用

2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Murugan, S. Patil, Shravani S. Shree Deeksha, V. Reddy, Rohith K. Shravanth Kumar, K.N. Dept. of Computer Science and Engineering Sri Venkateshwara College of Engineering Bengaluru562157 India Dept. of Computer Science and Engineering Sri Venkateshwara College of Engineering Bengaluru56215 India

ISBN: (纸本)9798350383867

The emergence of deep learning methods in medical image analysis has transformed the detection and categorization of bone tumors, presenting encouraging pathways for enhanced diagnosis and treatment strategizing. This literature review synthesizes recent advancements in utilizing deep learning architectures, particularly convolutional neural networks (CNNs), for the automatic interpretation of various imaging modalities including X-rays, CT scans, MRI scans, and bone scintigrams in the context of bone cancer detection and classification. Each study discussed presents unique methodologies combining traditional image processing techniques also the augmentation techniques with deep learning models to accurately identify, categorize, and segment bone lesions. Despite the encouraging results in terms of accuracy, sensitivity, and specificity, several common limitations are identified across the studies, including small sample sizes, potential biases, limited validation on diverse datasets, and a lack of thorough comparisons with existing techniques or expert interpretations. Addressing these limitations through larger and more diverse datasets, rigorous validation protocols, uncertainty quantification, and consideration of clinical outcomes would enhance the reliability, generalizability, and clinical utility of the proposed deep learning-based methodologies. Overall, these studies underscore the immense potential of deep learning approaches in advancing the field of bone cancer diagnosis and management, paving the way for more robust and clinically applicable tools to assist medical professionals. ©2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient LEDCA Analysis for Improved Throughput in Wireless Sensor Networks 6

Energy Efficient LEDCA Analysis for Improved Throughput in W...

引用

6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Padmageetha, B.G. Naik, Pramod Kumar Patil, Mallanagouda Dept.of Computer Applications Dayananda Sagar University Bengaluru India Dept. of Computer science and Engineering Dayananda Sagar University Bengaluru India Dept. of Computer science and Engineering RVITM Bengaluru India

ISBN: (纸本)9798331522667

Wireless Sensor Networks (WSNs) face significant challenges in terms of energy conservation, scalability, and data throughput owing to their limited node energy resources. This paper presents a low-energy data-centric algorithm (LEDCA), a novel energy-aware clustering and routing protocol designed to optimize energy efficiency and improve throughput in WSNs. Through simulations, LEDCA demonstrated a Packet Delivery Ratio (PDR) of up to 90%, throughput of 255,217 bps, and average latency of 159 ms, validating its efficiency in resource-constrained environments. The algorithm integrates residual energy awareness by prioritizing high-energy nodes for Cluster Head (CH) roles, dynamically adjusting routing paths, and balancing the network load to prevent premature node failure. By applying an Energy Mapping Node and a real-time Energy Mapping Table, LEDCA minimizes re-clustering, reduces data redundancy, and ensures stable data transmission even under high-density networks. Simulation results also show LEDCA's scalability of LEDCA, with A9_T_200 achieving the highest throughput under extended transmission ranges and A3_T_200 achieving the lowest latency, making it suitable for energy-sensitive and latency-critical applications. Future enhancements, such as integrating Non-Orthogonal Multiple Access (NOMA) and dynamic resource allocation, could further improve LEDCA’s interference management and scalability of LEDCA for IoT and 5G/6G networks, addressing the needs of next-generation applications. © 2025 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Detection of Vehicle Crashes on Roads using Deep Learning 2

Detection of Vehicle Crashes on Roads using Deep Learning

引用

2nd International Conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Pokkuluri, Kiran Sree Sssn Usha Devi, N. Prasad, M. Raja Rao, Pbv Varma, Ch Phaneedra Ramesh Babu, G. Shri Vishnu Engineering College for Women Dept. of Computer Science and Engineering Bhimavaram India University College of Engineering College Dept. of Computer Science and Engineering JNTU Kakinada India

ISBN: (纸本)9798350371314

As the modern life is highly dependent on the modern transport system, road safety became a high priority. Most of the systems are aiming for very less reporting time to reduce the severity of the accidents. This paper presents an in-dept. analysis of crash detection on roads using deep learning(DL). We have use one of the mechanisms of deepening i.e. Convolutional Neural Networks (CNNs) to detect the same. These DL models are used to classify the traffic accidents and it automatically recognize accidents with minimum effort. We have integrated automatic SMS alert with the system, which send SMS automatically after detecting the crash. This feature enhances the acceleration of emergency response, which makes the system more robust. We have achieved an accuracy of 96.3% which relatively good compared with the existing baseline methods. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Image Partitioning and Compression Mechanisms 15

A Comparative Analysis of Image Partitioning and Compression...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Chaudhari, Sampada P. Thakur, Nileshsingh V. Dept. of Computer Science and Engineering Prof Ram Meghe College of Engineering & Management Badnera India Dept. of Computer Science and Engineering Yeshwantrao Chavan College of Engineering Nagpur India

ISBN: (纸本)9798331300579

This paper presents a comprehensive comparative analysis of image partitioning and compression mechanisms, two fundamental techniques in image processing and data compression. Image partitioning involves dividing an image into smaller components, while compression aims to reduce the size of digital images while preserving visual quality. The analysis encompasses various aspects of both techniques, including methodologies, algorithms, and performance metrics. For image partitioning, segmentation methods such as block-based, region-based, and hierarchical partitioning are examined, along with their respective advantages and limitations. Additionally, the paper explores compression mechanisms such as transform coding, quantization, entropy coding, and predictive coding, highlighting their roles in achieving efficient compression. Furthermore, the comparative analysis evaluates the tradeoffs between different partitioning and compression techniques in terms of compression ratio, image quality, computational complexity, and applicability across different types of images and applications. Various compression standards such as JPEG and PNG are also reviewed to provide insights into real-world implementations. Finally, the paper discusses future research directions and emerging trends in image partitioning and compression, including the integration of machine learning techniques for improved segmentation and compression performance. The findings presented in this comparative analysis can serve as a valuable resource for researchers, practitioners, and developers working in the fields of image processing, data compression, and multimedia systems. © Grenze Scientific Society, 2024.

关键词： Image compression

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Deep Learning Models in Driver Behavior Recognition

Performance Analysis of Deep Learning Models in Driver Behav...

引用

2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Kapoor, Rameshwari Kuliyal, Rashmi Bhanot, Nilesh Bagla, Piyush Rawat, Ruchira Graphic Era Hill University Dept. of Computer Science and Engineering Uttarakhand Dehradun India University Dept. of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798331542344

The World Health Organization report states that nearly 1.25 million people lose their lives due to an increasing number of road accidents every year. The majority of accidents are reported due to driver errors, which include distractions like the use of mobile phones and fatigue, which causes drowsiness. This study aims to address these issues by performing a comparative analysis between different deep learning models representing two types of learning mechanisms: Traditional deep learning and transfer learning. This study portrays the use of two datasets to accomplish this task. These two datasets are the Driver Drowsiness Dataset DDD and the State Farm Distracted Drivers Dataset. The purpose of this investigative research is to explore the execution and efficiency differences between three deep learning algorithms, the traditional convolutional neural network, ResNet50, and VGG16, in classifying driver behavior by training these models individually on both datasets. This study also targets developing an alarm system that sounds an alarm based on a threshold by using an ensemble of all the models trained for comparative study and averaging their predictions to classify driver behavior. VGG16 achieved an accuracy of 99.74% on the driver drowsiness dataset, whereas Custom CNN Architecture achieved an accuracy of 98.70% on the driver distraction dataset. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Approach Using Cryptography and K-Least Significant Bit Steganography Algorithm in Cloud Computing 1

A Hybrid Approach Using Cryptography and K-Least Significant...

引用

1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Goyal, Anshika Gupta, Bhumika VMSB Uttarakhand Technical University Dept. of Computer Science & Engineering Dehradun India G.B. Pant Institute of Engineering & Technology Dept. of Computer Science & Engineering Pauri India

ISBN: (纸本)9798331518578

The exponential growth of communication technologies has broadened the cloud computing ecosystem horizon to meet main communication needs. However, in-parallel upsurge in online attacks has alarmed industries to ensure optimal data security. The combination of steganography and cryptosystems has been recognized as an enhanced security model for data transfer among the main security systems now in use. In this paper, a hybrid approach using cryptography and K- Least Significant Bit Steganography algorithm in Cloud Computing (HYBC-KLSBS-CC) are proposed. Initially, input text data is retrieved from cloud storage and compressed using Huffman Compression Coding (HCC) to reduce data size. The compressed data is then encrypted with a Hybrid Cryptography Algorithm (Hyb-MRFC-ALC), combining Modified Random Fibonacci Cryptography and Asymmetric Lightweight Cryptography to ensure robust encryption. Finally, encrypted data is embedded within an image using the K-Least Significant Bit (KLSB) steganography technique, providing additional layer of security. The proposed method enhances data confidentiality, integrity, and storage efficiency in cloud environments. The proposed HYBC-KLSBS-CC approach attains 26.89%, 29.49% and 18.64% lower PSNR and 26.89%, 29.49% and 18.64% lower MSE when analyzed through existing techniques like data security dependent on cryptography steganography related with OTP procedure and Huffman coding in the cloud environment (CS-OTP-CE), a novel hybrid cryptographic framework for secure data storage in cloud computing: Integrating AES-OTP and RSA with adaptive key management and Time-Limited access control (AES-OTP-RSA-CC) and Crypto-Stegno dependent model for securing medical information on IOMT platform (CS-SMI-IOMT). © 2025 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Power Control of Preamble Transmission for Grant-free Random Access in Cell-Free IoT Networks 15

Power Control of Preamble Transmission for Grant-free Random...

引用

15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Youn, Jiseung Cho, Sunghyun Hanyang University Dept. of Computer Science & Engineering Seoul Korea Republic of Hanyang University ERICA Dept. of Computer Science & Engineering Ansan Korea Republic of

ISBN: (纸本)9798350364637

As Internet of Things (IoT) technologies are inves-tigated to support key 5G services, significant research efforts are being made to enable machine-type communication (MTC). Cell-free IoT (CF-IoT) systems, characterized by favorable prop-agation and macro diversity, are being studied in conjunction with grant-free random access (GFRA) as a potential enabler to achieve massive connectivity for MTC. However, existing GFRA schemes in CF-IoT transmit preambles at a fixed power level resulting in severe preamble collisions at nearby access points (APs). In this paper, we analyzes the analysis of preamble collisions in massive connectivity scenario and proposes a sim-ple power control scheme to address preamble collision. The proposed scheme mitigates preamble collisions by transmitting preambles only to the nearest AP in high-density access scenes. Simulation results show that the proposed method improves the random access success rate compare to existing GFRA method by 10%. © 2024 IEEE.

关键词： cell-free massive MIMO grant-free random access Internet of Things power control

来源：评论

学校读者我要写书评

暂无评论

Quantitative Trends Analysis on Russian Literature Research in Korean Academia: Insights from KCI Data 10

Quantitative Trends Analysis on Russian Literature Research ...

引用

10th International Conference on Platform Technology and Service, PlatCon 2024

作者： Iosifovich, Ten Alexander Yeo, Sang-Soo Jung, Young-Ae Dept. of Computer Science Sun Moon University Asan Korea Republic of Dept. of Computer Engineering Mokwon University Daejeon Korea Republic of Dept. of AI Software Technology Sun Moon University Asan Korea Republic of

ISBN: (纸本)9798350367874

This paper presents a quantitative analysis of trends in Russian literature and Korean-Russian translated literature within Korean academia from 1996 to 2024. By analyzing frequency themes and contexts, the study explores evolving research trends, revealing how sociocultural, political, and artistic exchanges between Korea and Russia have influenced each other. Future research using text mining promises to uncover more specific patterns, offering deeper insights into literary and cultural exchanges. This study contributes to understanding the role of literature in expressing and understanding sociopolitical and cultural values in both countries. © 2024 IEEE.

关键词： Korean Citation Index Korean-Russian literature Quantitative analysis Research trend analysis Text mining

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 << < 10 11 12 13 14 15 16 17 18 19 > >>

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：