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

1,594 篇 会议
596 篇 期刊文献
1 册 图书

馆藏范围

2,191 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,198 篇 工学
- 920 篇 计算机科学与技术...
- 787 篇 软件工程
- 287 篇 信息与通信工程
- 229 篇 控制科学与工程
- 184 篇 生物工程
- 169 篇 生物医学工程（可授...
- 164 篇 电气工程
- 136 篇 光学工程
- 101 篇 电子科学与技术（可...
- 98 篇 网络空间安全
- 94 篇 安全科学与工程
- 71 篇 机械工程
- 71 篇 仪器科学与技术
- 63 篇 交通运输工程
- 56 篇 化学工程与技术
- 55 篇 动力工程及工程热...
687 篇 理学
- 336 篇 数学
- 215 篇 生物学
- 189 篇 物理学
- 145 篇 统计学（可授理学、...
- 93 篇 化学
349 篇 管理学
- 235 篇 管理科学与工程(可...
- 143 篇 图书情报与档案管...
- 123 篇 工商管理
186 篇 医学
- 144 篇 临床医学
- 139 篇 基础医学(可授医学...
- 110 篇 公共卫生与预防医...
- 75 篇 药学(可授医学、理...
79 篇 法学
- 70 篇 社会学
56 篇 经济学
- 56 篇 应用经济学
51 篇 农学
26 篇 教育学
15 篇 文学
2 篇 军事学
1 篇 哲学
1 篇 历史学
1 篇 艺术学

主题

210 篇 accuracy
136 篇 deep learning
128 篇 real-time system...
106 篇 machine learning
99 篇 convolutional ne...
87 篇 training
85 篇 predictive model...
74 篇 feature extracti...
70 篇 computational mo...
66 篇 medical services
62 篇 support vector m...
62 篇 data models
61 篇 machine learning...
58 篇 optimization
55 篇 internet of thin...
53 篇 reliability
43 篇 reviews
42 篇 monitoring
42 篇 technological in...
41 篇 prediction algor...

机构

59 篇 nitte meenakshi ...
51 篇 department of ar...
41 篇 lovely professio...
31 篇 department of ar...
31 篇 department of co...
29 篇 lamarr institute...
25 篇 machine learning...
24 篇 rajalakshmi engi...
21 篇 department of ar...
21 篇 machine learning...
21 篇 machine learning...
21 篇 department of ar...
20 篇 department of ar...
20 篇 machine learning...
19 篇 the lamarr insti...
19 篇 department of ph...
19 篇 east west instit...
19 篇 department of co...
19 篇 new horizon coll...
18 篇 the department o...

作者

61 篇 müller klaus-rob...
50 篇 piyush kumar par...
47 篇 pareek piyush ku...
39 篇 mohsen guizani
36 篇 prateek verma
29 篇 guizani mohsen
26 篇 stachniss cyrill
25 篇 zhang kun
24 篇 verma prateek
18 篇 behley jens
16 篇 uma reddy
16 篇 vijay k.
15 篇 cyrill stachniss
15 篇 montavon grégoir...
14 篇 amandeep nagpal
13 篇 von lilienfeld o...
13 篇 nakajima shinich...
12 篇 aditya barhate
12 篇 madhura g.k.
12 篇 cai ruichu

语言

1,810 篇 英文
377 篇 其他
5 篇 中文

检索条件"机构=Department of artificial intelligence and Machine Learning"

共 2191 条记录，以下是11-20 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：

Smartsight: Android-Based Retinal Disease Detection using Retinal Fundus Images with XAI 8

Smartsight: Android-Based Retinal Disease Detection using Re...

引用

8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Bagewadi, Manisha Reshmi, B.M. Kalligud, Nagaraj Badiger, Krutika Sonagaj, Sakshi Giraddi, Sindurani Basaveshwar Engineering College Department of Artificial Intelligence and Machine Learning Bagalkot India

ISBN: (纸本)9798331505462

Diabetic retinopathy (DR) is a serious eye condition affecting diabetic patients, stemming from microvascular damage to retinal blood vessels. If not diagnosed and treated early, DR can lead to blindness. Traditional diagnostic methods involve manual examination of retinal images by ophthalmologists, which is labor-intensive and time-consuming. This highlights the need for automated, efficient, and accurate diagnostic tools. This study proposes a deep learning-based framework using ResNet50 architecture enhanced with Gradient-weighted Class Activation Mapping (Grad-CAM) for the automatic detection and classification of diabetic retinopathy from retinal images obtained via a smartphone-based fundus camera. The ResNet50 model, known for its deep residual learning capabilities, was trained on a dataset of retinal images to differentiate between healthy and DR-affected eyes. Incorporating Grad-CAM provides visual explanations by highlighting the retinal image regions most indicative of DR, thereby improving model interpretability. The proposed model demonstrated high performance, achieving 98% accuracy on the training dataset, 91% on the validation dataset, and 96% on the test dataset. These results highlight the model's robustness and potential for facilitating early DR detection, especially in resource-constrained environments with limited access to specialized ophthalmic care. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Insight Retina: A Deep learning Approach to Diagnose Diabetic Retinopathy

Insight Retina: A Deep Learning Approach to Diagnose Diabeti...

引用

2024 International Conference on Knowledge Engineering and Communication Systems, ICKECS 2024

作者： Akshaya, V. Sashank, S. Subhash, G.M. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798350359688

The greatest cause of blindness in the world and a frequent cause of diabetes melitus is Diabetic-Retinopathy (DR). To stop vision loss in afflicted people, early identification and decision making are essential. Diabetic - Retinopathy is a eye disorder that is currently being diagnosed manually by ophthalmologists. The diagnosis and recovery takes a great deal of time, effort and money, sometimes even a risk of misdiagnosis. Deep-learning has been the most highly emerging popular method that performs better in many fields, especially in the process analysing data and as well as classifying images from medical imaging. The IdX-DR and EyeArt AI are some existing systems that are legally approved and widely used in many places. Convolution neural networks and transfer learning are widely used as they are more effective. The dataset called Asia Pacific Tele-Ophthalmology Society (APTOS) is a large collection, which contains images acquired using Fundus Imaging and is available in open-source which is used extensively. The Insight Retina uses Contrast Limited Adaptive Histogram Equalization for enhancement of images and pre-trained model Res-Net for detection, thus providing improved performance and a reliable 0.893 Kappa accuracy score from the DR model. Insight Retina then generates a report for the input image providing accurate information about the stage of the Diabetic-Retinopathy. © 2024 IEEE.

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

Determining the Underlying Factors of Chronic Liver Disease through Factor Analysis 2

Determining the Underlying Factors of Chronic Liver Disease ...

引用

2nd International Conference on artificial intelligence and machine learning Applications, AIMLA 2024

作者： Balaji, V.S. Mahi, A.R. Aashif, M. Manju, M. Indira Priya, P. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349221

Chronic liver disease is a significant health concern, necessitating a comprehensive understanding of its underlying causes. The work aims to identify the key factors contributing to chronic liver disease using Factor Analysis, a statistical technique that explores the inter-relationships among a set of variables. The dataset, comprising various biochemical parameters and demographic details, is subjected to rigorous preprocessing, including imputation and standardisation. The suitability of data is determined using KMO measure value. The factors are represented by combinations of things that include the biochemical parameters protein, aminotransferase, globulin, phosphatase and *** research provides valuable insights, potentially aiding in early diagnosis and effective treatment strategies for chronic liver disease. This research underscores the utility of Factor Analysis in medical research, particularly in understanding complex diseases like chronic liver disease. The overview of Factor Analysis would include the loadings of each factor for each variable on each factor, which indicate how much each variable contributes to each factor and further help to identify which variables are most strongly associated with each underlying factor. The communalities and specific variances of the factors are *** could potentially aid in early diagnosis and effective treatment strategies for chronic liver disease. The complex relationship among various attributes of the dataset is examined thereby providing the contribution of a vital parameter to liver disease. © 2024 IEEE.

关键词： Factor analysis

来源：评论

学校读者我要写书评

暂无评论

Novel Multi-Stage Multi-Task Deep learning Framework for the Cybersecurity of In-Vehicle Networks 8

Novel Multi-Stage Multi-Task Deep Learning Framework for the...

引用

8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Shirole, Vaibhav Sunil Mahesh Madhnani, Harsh Bhojane, Niranjan Umakant Nandhini, K. Gite, Shilpa Symbiosis Institute of Technology Department of Artificial Intelligence and Machine Learning Pune India

ISBN: (纸本)9798350391770

Objective - To develop a deep learning-based robust threat detection system for in-vehicle networks of autonomous vehicles to differentiate normal vehicle operation from potential *** - The Controller Area Network (CAN) network traffic dataset, including both attack and normal messages, was used for the study. Several features were present in this dataset, including class and subclass designations that help to differentiate between legitimate operational signals and possible attack messages. Feature engineering techniques were applied to the dataset. Data preparation was done after feature engineering, with the main goal being to make it ready to train the *** pre-processing the data, three distinct neural network architectures were applied utilizing a multi-task and multi-stage approach: convolutional neural network, long short-term memory, and artificial neural network. The most appropriate and useful model for the specific context was then identified by comparing the accuracies of different *** - With a multistage approach, the convolutional neural network model demonstrated remarkable training accuracies of 98.10% for Stage I (classifying attack or normal condition) and 99.08% for Stage II (classifying type of attack). Also, the Stage I and Stage II testing accuracies were 98.08% and 99.09% © 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

Advanced Sound Detection and Behavior Examination for Real-Time Intruder Detection using Deep learning: A Comprehensive Security Framework 2

Advanced Sound Detection and Behavior Examination for Real-T...

引用

2nd International Conference on artificial intelligence and machine learning Applications, AIMLA 2024

作者： Harini, B. Gouri, M.P. Balaji, V.S. Sangeetha, K. Harshini, A. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349221

The system responds to escalating security concerns with a sophisticated intruder detection system, integrating glass-breaking sound detection and behavior analysis. Using audio sensors and advanced signal processing, it prioritizes detecting glass-breaking events for scenarios involving forced entry through windows or glass doors. Behavior examination and analysis employs deep learning for real-time monitoring, alerting to suspicious activities. Immediate notifications are sent to security personnel or homeowners. Designed with privacy-preserving techniques, it adapts to diverse environments, customizable for various security needs and integrates with existing infrastructure. Representing a significant security advancement, it combines sound detection, behavior analysis, and real-time alerting, prioritizing ethical considerations and privacy preservation. This project paves the way for a safer future. © 2024 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Drug Review: Sentiment Analysis, Using Advanced machine learning

Drug Review: Sentiment Analysis, Using Advanced Machine Lear...

引用

2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Akshaya, V. Raja Ruben, B. Santhosh, K. Shafiya Banu, M. Rajalakshmi Engineering College Department Of Artificial Intelligence And Machine Learning Chennai India

ISBN: (纸本)9798350352689

'Sentiment Analysis of Drug Reviews Using machine learning Techniques,' focuses on employing advanced machine learning methods, including Bidirectional LSTM and TF-IDF, to analyze sentiments expressed in clinical drug reviews. The aim is to develop sentiment analysis model capable of classifying and describing the patient experiences with medications. the usage of Bidirectional LSTM architecture to capture contextual dependencies within sequential data, enhancing the accuracy of sentiment predictions is used. Additionally, the TF-IDF technique is employed for feature extraction, emphasizing the importance of sentiments of patients and addressing some challenges due to language. The performance results obtained during evaluation of the model contains an accuracy of 94.21%. Thus, the usage of these techniques aims to provide a comprehensive understanding of sentiment patterns in clinical drug reviews, offering valuable insights for healthcare professionals. © 2024 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

SecureGenKeys: Building Secure and Personalized Keypads with Generative AI 10

SecureGenKeys: Building Secure and Personalized Keypads with...

引用

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Vamsikeshwaran, M. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

Ensuring the security of systems is paramount in safeguarding confidential information from unauthorized access, particularly in today's interconnected digital landscape. Visual eavesdropping techniques, such as 'Shoulder Surfing,' pose significant threats to security, including unauthorized access, data breaches, and identity theft, whereby sensitive information is illicitly obtained during user input. This paper introduces a novel method designed to fortify password security, simultaneously enhancing the user experience and facilitating secure transactions. The proposed methodology introduces a personalized interactive password selection process that not only increases user engagement but also bolsters security measures. User-entered prompts undergo processing to transform into personalized tokens and form a secure password. These tokens are utilized to generate foundational images in which the tokens are strategically allocated ensuring both clarity and randomness. The system employs machine learning algorithm, particularly focusing on deep learning approaches for image analysis and pattern recognition techniques to verify user-entered passwords against stored data. Successful authentication triggers secure transactions, providing a seamless and protected user experience. © 2024 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Voice Genius : IT's Echoes of intelligence 15

Voice Genius : IT's Echoes of Intelligence

引用

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

作者： John, Ayain Shreerama, D.S. Shreyas, S. Sagar, U. Prajwal Dayananda Sagar University Department of Artificial Intelligence & Machine Learning Bangalore India

ISBN: (纸本)9798350370249

The dynamic technology of today requires a framework that makes task automation simple. This study presents a unique AI helper that can have conversations that go beyond voice orders. With the use of sophisticated voice synthesis and speech recognition, this intelligent system can comprehend user input and react appropriately. Imagine using an integrated speaker to ask questions like 'How's traffic?' or 'What's the weather?' and getting quick, tailored answers. Because of its user-friendly interface, manual interaction is eliminated, allowing for hands-free ease. The assistant's capacity for learning and adaptation also guarantees ongoing development, which improves user experience even more. This work paves the path for a time when people will be able to use technology to help them naturally achieve their goals because it represents a major development in conversational AI. © 2024 IEEE.

关键词： API CNN & RNN Conversational AI IDE NLP(Natural Language Processing) speech synthesis techniques wake-word detection

来源：评论

学校读者我要写书评

暂无评论

Identification of Potholes and Speed Bumps Using SSD and YOLO 15th

Identification of Potholes and Speed Bumps Using SSD and YOL...

引用

15th International Conference on Intelligent Computing and Networking, IC-ICN 2024

作者： Chandak, Payal Chaurasia, Shivamkumar Patil, Megharani Department of Artificial Intelligence and Machine Learning Thakur College of Engineering and Technology Mumbai India

ISBN: (纸本)9789819786305

Using SSD and YOLO to efficiently detect potholes and speed bumps is the main goal of this project, which aims to improve road safety and construction quality. Hazard priority is emphasized and the limitations of the manual method are addressed. YOLO and SSD architectures are used, trained, and optimized on a variety of datasets with different road appearances and conditions. To improve model capabilities, data augmentation approaches are used. The study explores techniques for processing data quickly through optimization. Accuracy, recall, and efficacy are measured by gathering large amounts of data, training models, and assessing results on different test sets. Extensive analysis between YOLOv4 and SSD-MobileNet demonstrates clear differences in performance. YOLOv4 achieves an overall improved object detection proficiency of 85.48, a superior mAP@0.5 score. By comparison, SSD-MobileNet demonstrates unique metric strengths in precision (0.42), recall (0.81), and F1 score (0.82). In particular, SSD-MobileNet significantly outperforms YOLOv4 (52.51 ms) in inference time (7 ms), demonstrating its effectiveness in real-time applications. The study suggests using SSD-MobileNet because of its excellent F1 score, repeatability, and precision for real-time applications. Because of its quick inference time, this model is a great fit for high-stakes situations where accurate and timely object identification is necessary, such as security systems, drones, and autonomous cars. It also balances performance measurements with practicality. Novelty: By utilizing cutting-edge computer vision techniques, this study creatively combines SSD and YOLO to produce a safer and more effective method of infrastructure management and road danger monitoring. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Emotion Trajectories in Cinematic Narratives: A Transformer-Based Analysis 1

Emotion Trajectories in Cinematic Narratives: A Transformer-...

引用

1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Sudabathula, Vijay Sai Kumar Naik, Banoth Krishna Mohan Ismail, Shifa Mattaparty, Sri Harsh Arora, Gagan Deep Yadav, Guda Sravan Vardhaman College of Engineering Department of Artificial Intelligence & Machine Learning Hyderabad India

ISBN: (纸本)9798350352931

This paper introduces a novel method for analyzing movie dialogues to predict characters' primary emotions and the overall emotional tone of a film. Using natural language processing, we assess dialogues across emotional dimensions such as happiness, sadness, anger, fear, and more. Our approach involves collecting and preprocessing movie scripts, followed by building emotion classification models. By examining the context, sentiment, and linguistic features of dialogues, we predict character emotions and aggregate them to map the emotional trajectory of the movie. Diverging from traditional rating prediction models, our method aligns emotional experiences from movie scripts with reviewer feedback for improved accuracy. We also propose a sentimentbased movie recommender system that matches users' emotions with film sentiments, offering a unique alternative to existing recommendation systems. Through extensive evaluation, our approach contributes to affective computing and provides deeper insights into the emotional structure of cinematic narratives. © 2024 IEEE.

关键词： Decision trees

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220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：