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

30,252 篇 会议
4,791 篇 期刊文献
239 册 图书

馆藏范围

35,282 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21,843 篇 工学
- 15,817 篇 计算机科学与技术...
- 13,300 篇 软件工程
- 5,834 篇 信息与通信工程
- 3,443 篇 控制科学与工程
- 2,663 篇 电子科学与技术（可...
- 2,616 篇 电气工程
- 2,370 篇 生物工程
- 1,904 篇 生物医学工程（可授...
- 1,538 篇 光学工程
- 1,344 篇 机械工程
- 1,218 篇 动力工程及工程热...
- 1,202 篇 仪器科学与技术
- 1,014 篇 化学工程与技术
- 865 篇 安全科学与工程
- 738 篇 交通运输工程
11,214 篇 理学
- 6,082 篇 数学
- 3,048 篇 物理学
- 2,594 篇 生物学
- 2,026 篇 统计学（可授理学、...
- 1,325 篇 系统科学
- 1,084 篇 化学
5,669 篇 管理学
- 3,301 篇 管理科学与工程(可...
- 2,649 篇 图书情报与档案管...
- 1,823 篇 工商管理
1,620 篇 医学
- 1,402 篇 临床医学
- 1,310 篇 基础医学(可授医学...
- 865 篇 药学(可授医学、理...
- 684 篇 公共卫生与预防医...
1,042 篇 法学
- 840 篇 社会学
649 篇 经济学
- 649 篇 应用经济学
491 篇 农学
425 篇 教育学
158 篇 文学
79 篇 军事学
39 篇 艺术学
2 篇 哲学

主题

1,094 篇 accuracy
855 篇 feature extracti...
842 篇 computational mo...
715 篇 deep learning
685 篇 training
676 篇 computer science
535 篇 machine learning
527 篇 real-time system...
520 篇 support vector m...
467 篇 predictive model...
417 篇 internet of thin...
351 篇 convolutional ne...
347 篇 computer archite...
344 篇 data models
329 篇 reliability
303 篇 optimization
296 篇 data mining
275 篇 routing
260 篇 wireless sensor ...
248 篇 artificial intel...

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
77 篇 institute of inf...
76 篇 infn sezione di ...
74 篇 tno technical sc...
66 篇 università di ca...
65 篇 université de st...
64 篇 dept. of informa...
60 篇 nikhef national ...
58 篇 dept. of informa...
58 篇 dept. of compute...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
49 篇 dept. of compute...
48 篇 dept. of compute...
46 篇 university würzb...
45 篇 dept. of electri...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
82 篇 chen a.
82 篇 kalekin o.
79 篇 díaz a.f.
78 篇 boumaaza j.
78 篇 coleiro a.
76 篇 gozzini s.r.
68 篇 huang f.
68 篇 dallier r.
62 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

34,021 篇 英文
847 篇 其他
309 篇 中文
56 篇 日文
50 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 Computer Science and Engineering With Data Science"

共 35282 条记录，以下是121-130 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：

Parallelized 0/1 Knapsack Algorithm Optimization in CPU-GPU-Based Heterogeneous System with Algorithm-based Fault Tolerance 18

Parallelized 0/1 Knapsack Algorithm Optimization in CPU-GPU-...

引用

18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Abid, Marzan Binte Shaha, Shuvo Kabir, Upama Arefin, Md. Fahim University of Dhaka Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350331011

A heterogeneous high-performance computing (HPC) system is an aggregation of CPUs and GPUs through high-speed interconnection. As graphics processing units (GPUs) can conduct rapid mathematical and vector operations due to their hardware properties, GPU-based heterogeneous systems can optimize algorithms that show data parallelism. Since the dynamic programming (DP) solution of the 0/1 knapsack algorithm is inherently data-parallel, this paper optimized the algorithm to maximize the advantages of a GPU-based parallel environment. Furthermore, this research identified that the algorithm was well suited to four distinct GPU-launch approaches. Among them, the "single-cell calculation by single thread with a single kernel launch"approach outperforms others by reducing the complexity from O(n∗w) to O(n). Besides, these HPC systems are susceptible to the slightest of errors. Checkpoint recovery (CP/R) is the most commonly used fault tolerance and recovery system, which suffers from huge checkpoint and recovery overhead. To reduce this overhead in CPU-GPU-based heterogeneous systems, an algorithm-based fault tolerance (ABFT) technique has been proposed for a particular class of algorithm: 0/1 knapsack. The experimental results verify the feasibility of the proposed ABFT technique and demonstrate that the system can recover from failures with minimal overhead. © 2024 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Real-Time Dashboarding using Big data Tools 7

Real-Time Dashboarding using Big Data Tools

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Sanjay, R. Pulakhandam, Dheeraj Nirmalrani, V. Sathyabama Institute of Science And Technology Dept. Computer Science And Engineering Chennai India

ISBN: (纸本)9798350359299

Real-time dashboarding software empowers organizations to harness the burgeoning IoT data stream, transforming raw sensor readings into actionable insights through a secure and scalable architecture. data from connected devices seamlessly flows via lightweight protocols like MQTT and is managed by a robust streaming platform like Kafka. Big data tools like Spark then extract meaning from this high-velocity data, preparing it for visualization on dynamic dashboards hosted by cloud platforms. These user-centric dashboards track key metrics, identify trends, and drive informed decision-making, but tackling challenges like scalability, security, and data quality is crucial to unlock the full potential of this transformative technology. © 2024 IEEE.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

Effective Polyp Segmentation in Medical Imaging: A Semi-Supervised Approach with Progressive Supervision 3

Effective Polyp Segmentation in Medical Imaging: A Semi-Supe...

引用

3rd International Conference on Big data, Information and computer Network, BDICN 2024

作者： Ye, Shunlong Ji, Zexuan Nanjing University of Science and Technology Dept. of Computer Science and Engineering Nanjing China

ISBN: (纸本)9798350363821

Medical imaging plays a pivotal role in diagnosing and monitoring various diseases, and accurate polyp segmentation is essential for early disease detection and treatment planning. However, the scarcity of well-Annotated medical imaging data hampers the development of effective segmentation models. Semi-supervised learning stands out as a critical approach to address this issue. Traditional semi-supervised medical image segmentation models leverage strong-weak perturbation consistency losses to provide supervision signals. While these losses are effective in promoting consistency, they often exhibit a drawback, that is the dominance of strong perturbations during early training stages. This dominance hinders the model's ability to extract meaningful features, ultimately impacting its overall performance. In response to these challenges, we introduce a novel training method applied to polyp segmentation. We employ a progressive approach, gradually introducing strong-weak perturbation supervision signals. This gradual guidance empowers the model to focus on learning relevant features from the beginning of training, mitigating the issue of early dominance and enhancing its performance. Our method is evaluated on two widely-used polyp segmentation datasets and surpasses state-of-The-Art methods, demonstrating substantial improvements in segmentation accuracy. © 2024 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Fabric Defect Detection using Deep Learning 3

Fabric Defect Detection using Deep Learning

引用

3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Kailasam, Khushi Singh, Jaswant Gopika, G.S. Sreekrishna, M. Supriya, S. Sathyabama Institute of Science and Technology Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350396157

Fabric defect detection plays a crucial role in the textile manufacturing industry's quality control process since it guarantees that customers will receive perfect products. Deep Learning (DL) models have demonstrated a great deal of promise in recent years for accurately identifying fabric defects. The proposed fabric defect identification method combines the best features of two architectures: You Only Look Once (YOLOv4) and Region-based Convolutional Neural Network (R-CNN). While YOLOv4 offers quicker and more effective detection, R-CNN generates region recommendations that allow accurate localization of fabric defects. There are two stages in the proposed system. Initially, region proposals are detected using the R-CNN feature extractor and then a convolutional neural network is used for defect classification. YOLOv4 is used for performing object detection in the second step, where the flaws are concurrently classified and localized. The tests carried out on a fabric defect dataset show that the proposed method outperforms the R-CNN and YOLOv4 models separately. The proposed system is appropriate for real-Time fabric flaw detection applications in a variety of sectors due to its high detection accuracy and quick processing time. This study demonstrates how well R-CNN and YOLOv4 together work for fabric flaw detection, providing hope for future developments in the area. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Smart Barcode Scanning using X-ray Technology with computer Vision and Machine Learning 4

Smart Barcode Scanning using X-ray Technology with Computer ...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Vijayaraj, J. Hari Yogith, S. Rithikravivarma, V. Siddharth, S. Easwari Engineering College Dept. of Artificial Intelligence and Data Science Chennai India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523923

Barcode scanning errors in retail environments contribute to inventory discrepancies, financial losses, and inefficiencies in stock management. Traditional optical barcode scanning methods are prone to failures due to occlusion, poor lighting conditions, and barcode damage. While recent advancements such as computer vision, deep learning-based error detection, and RFID integration have improved scanning accuracy, these approaches still face challenges related to high computational requirements, environmental dependencies, and implementation costs. This paper proposes a novel method utilizing X-ray imaging technology and advanced machine learning algorithms to detect improperly scanned or missing barcodes in real time. The system captures detailed X-ray images of items as they enter retail stores or warehouses and applies deep learning models to analyze barcode visibility. Real-time alerts are generated when scanning anomalies are detected, enabling prompt corrective action. Experimental evaluations demonstrate that the proposed approach significantly improves barcode detection accuracy, enhances inventory management, and reduces operational costs. The findings highlight the potential for widespread deployment in retail and logistics environments, offering a robust solution to barcode scanning challenges. © 2025 IEEE.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Sparse Channel Estimation in Massive MIMO Systems Using Compressed Sensing and Neural Networks

Sparse Channel Estimation in Massive MIMO Systems Using Comp...

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

In this paper, based on compressed sensing and neural networks, we present an intelligent sparse channel estimation technique for Massive MIMO systems. We show that our approach improves considerably the estimation accuracy in terms of Mean Squared Error (MSE) and Normalized Mean Squared Error (NMSE) with respect to classical methods. We demonstrate [Figure: ] that our approach is computationally more efficient, requires less time and resources (memory/disk) compared to the existing literature but for a robustness of performance across distal or low Signal-to-Noise Ratios (SNRs). We also confirm our method exhibits fast convergence and efficiently accommodates a variety of sparsity levels. By visualizing it using heatmaps and ROC curves we show that this method is able to effectively differentiate between signal and noise, asserting our approach as a powerful tool for the contemporary set of problems present in wireless communications. © 2024 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Enhancing Early Detection of Pancreatic Cancer: A Machine Learning Approach with Explainable AI Insights

Enhancing Early Detection of Pancreatic Cancer: A Machine Le...

引用

2024 IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2024

作者： Pattanashetti, Neeraj V Mayur, R. Prakash, Adarsh Adiga, Tryambaka B Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Information Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India

ISBN: (纸本)9798350376876

Among the most deadly and complex illnesses in the world, pancreatic cancer is typified by its early asymptomatic stage and subsequent discovery of the disease when it has progressed to an advanced stage. Getting the patients in a correct treatment path at the earliest point is important for suitable intervention and patient outcomes in the long run. We utilized advanced algorithms and model prediction techniques includes, feature extraction, hyperparameter tuning and explainability methods which aims to enhance both the comprehension and predictive accuracy of models employed. The goal is to assess patient health status and diagnose pancreatic diseases (cancer vs. non-cancer) by developing a learning algorithm. We obtained a dataset containing demographic information and urine biomarkers to start the investigation. First stage of our analysis employs a single classifier and later we apply bagging and boosting algorithms to achieve ensemble models. Hyperparameter fine-tuning has got a positive outcome, which has Gradient Boosting and Cat Boosting as its top performing models. The ensemble model produced excellent results (92.02 %), demonstrating the usefulness of the suggested approach. LIME and SHAP techniques play the key role in model outcome interpretability providing an insight of algorithmic decision-making process. Such a wide range of combinations of biomarkers have a potential of pancreatic cancer detection in early stages and thus will help shape diagnostics strategies in near future. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Predicting Customer Purchase Intent Using Logistic Regression: A data-Driven Approach 2

Predicting Customer Purchase Intent Using Logistic Regressio...

引用

2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Rajarajachozhan, C. Karthika, G. Rajakrishnammal, A. Mano, M. Kumar, P. Nithish Jayahari, E. Saveetha Engineering College Dept. of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Engineering College Dept. of Artificial Intelligence and Data Science Tamil Nadu Chennai India Saveetha Engineering College Dept. of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331505745

Predicting customer purchase intent is crucial for modern businesses in order to improve engagement, refine marketing strategies, and increase revenue. Conventional rule-based systems encounter difficulties with dynamic and extensive customer data, limiting their flexibility and precision. This project employs a machine learning methodology utilizing logistic regression to forecast customer intent based on demographic, transactional, and behavioral data. The proposed model analyses input features including age, browsing history, and previous purchases, employing sophisticated data preprocessing methods such as One-Hot Encoding and feature scaling to guarantee data integrity. Through hyperparameter tuning and the assessment of critical metrics including accuracy, precision, recall, and Fl-score, the system provides dependable and actionable insights. Real-time predictive capabilities enable businesses to customize customer interactions, facilitating targeted marketing and enhancing customer experience. This project underscores the capacity of predictive analytics to tackle real-world issues, facilitating data-driven decision-making and sustainable business development. © 2025 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

A Detailed Analysis of Secrecy and Performance Metrics in Hybrid RF/ FSO Communication Systems: Implications of Composite Weibull and Log-normal Fading with M Turbulent Channels

A Detailed Analysis of Secrecy and Performance Metrics in Hy...

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

ISBN: (纸本)9798350379525

In this paper, we have analyzed the secrecy performance and system operation performance for hybrid RF/FSO systems against composite Weibull-log-normal fading channel with M turbulent channels. The performance is evaluated by carrying out extensive simulations to calculate Signal-to-Noise Ratio (SNR), Bit Error Rate (BER) and outage probability, we also re-evaluate channel capacity and secrecy capacity with respect of environmental conditions. Compared with RF only system, FSO only standalone scheme and some meaningful orthogonal-modulation multicarrier IM/DD-based schemes proposed by the literatures. Similarly, the utilization of adaptive modulation schemes improved resistance to fading and roughness in systems. The above results confirm the hybridization of both RF and FSO a comprehensive solution for dependable communication in different and even hostile surrounding conditions which set this work as reliable foundation point towards forthcoming research activity or application relevance within all range telecommunication sector. © 2024 IEEE.

关键词： Bit error rate

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning Approaches for Channel State Prediction in Heterogeneous Fading Networks

Transfer Learning Approaches for Channel State Prediction in...

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

ISBN: (纸本)9798350379525

In this work, we leverage state-of-the-art machine learning algorithms to predict Channel State Information (CSI), for enhancing performance of wireless communication systems. The simulation and analysis stop with transfer learning to finetune, adaptive domain adaptations, multitasking (MTL) as well a few shot meta-learning models framework under different network packet loss rate scenarios. By generalizing better from one domain to another, transfer learning pushes the performance beyond what traditional methods can obtain. Further, fine-tuning also helps to align the source and target domain distributions in feature space by a partial (or full) reduction of re-stylization error. This work proposes multi-Task learning as a tool to mitigate loses in light of predicting across fading scenarios. Considering multi-task learning also provides benefits from shared learnings, so experience is pooled between the tasks which indirectly improve prediction as well and it helps in training both of these algorithms together. Moreover, the few-shot learning models prove to be highly desirable as they deliver state-of-the-art performance with minimal training data for difficult problems. These results show the potential of AI-based methods to improve CSI prediction, and have implications for improving reliability and throughput when deploying real wireless communication systems. © 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 << < 9 10 11 12 13 14 15 16 17 18 > >>

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：