检索结果-内蒙古大学图书馆

Quantified emotion analysis based on design principles of color feature recognition in pictures

Multimedia Tools and Applications 2024年第19期83卷 57243-57267页

作者： Chen, Chin-Ling Huang, Qing-Yang Zhou, Ming Huang, Der-Chen Liu, Ling-Chun Deng, Yong-Yuan School of Information Engineering Changchun Sci-Tech University Jilin Province Changchun130600 China Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung City413310 Taiwan Xiamen Academy of Arts and Design Fuzhou University Fujian Xiamen361024 China School of Computer and Information Engineering Xiamen University of Technology Fujian Xiamen361024 China Department of Computer Science and Engineering National Chung-Hsing University Taichung402 Taiwan

When people observe pictures, different pictures will generate different emotions, and the painters often convey emotional energy to the audience through the media. Through the effect of this emotional transfer, people get emotional satisfaction psychologically, and the author can better express the emotion he needs to express by using the principle. For those who do not know art appreciation, it is difficult to accurately describe the feelings brought by pictures and describe them accurately. It is also difficult to quickly and accurately find the picture of the corresponding feeling sought by oneself. This paper presents a quantitative picture emotion analysis method. Based on the analysis of the characteristics and colors of the pictures that arouse people's emotions, the classification planning is carried out in RGB space and HSV color space respectively. And the combination analysis of the color features with strong influence is carried out to select a more appropriate color space for the expression of human feelings. At the same time, the paper also discusses the effect of the black-and-white filling and the brightness saturation of the image. Finally, it makes use of the corresponding design principles to carry out a quantitative analysis of the emotion generated by it. The system performs a combined analysis of a picture from these directions and presents the results to the user. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Recent Trends in Compact Planar Antennas at 5G Sub-6 GHz and mm Wave Frequency Bands for Automotive Wireless Applications: A Review

引用

Progress In Electromagnetics Research C 2024年 143卷 169-180页

作者： Kumar, Ashish Aljaidi, Mohammad Singh, Manpreet Alshammari, Mohammed Alsuwaylimi, Amjad A. Alenezi, Sami M. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science Faculty of Information Technology Zarqa University Zarqa13110 Jordan Department of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha91911 Saudi Arabia Department of Information Technology College of Computing and Information Technorlogy Northern Border University Arar91431 Saudi Arabia

5G wireless communication offers higher channel capacity, high data rate, sufficient bandwidth, enhanced coverage, and reliable link as compared to the previous generation mobile networks. Also, 5G becomes more relevant with the recent launches of low earth orbit satellites by various ventures like starlink, amazon, one web, etc. As these satellites have heights up to the range from 300 km to 1000 km, the free space path loss decreases drastically which in turn improves the signal reliability and efficient communication at dead spots. With these advancements, antenna researchers have the freedom to design compact, easy to manufacture, with adequate gain user equipment terminal antennas which can be easily integrated in the modern passenger car body. This paper will focus on the recent development in the design considerations of the compact antenna design at sub-6 GHz (n78 frequency band) and mm wave (n278 frequency band) according to 3gpp standards. This manuscript also discusses various design specifications like selection of material for antennas, design complexity, feeding methods, fabrication and measurement challenges and performance parameters which include reflection coefficient, gain, polarization, axial ratio, cross polarization discrimination, radiation efficiency, radiation pattern shape, etc. The proposed antenna design considerations will facilitate the possible integration into the various parts of the car body according to the recent vehicular applications for uninterrupted communication. © 2024, Electromagnetics Academy. All rights reserved.

关键词： Radiation efficiency

来源：评论

学校读者我要写书评

暂无评论

Optimizing the Performance of the ECLAT Algorithm using K-means Clustering for Frequently Itemset Mining for Large Datasets 5

Optimizing the Performance of the ECLAT Algorithm using K-me...

引用

5th International Conference on Advanced information Technologies, ICAIT 2024

作者： Lin, Nandar Win, Thanda Yangon Technological University Computer Engineering and Information Technology Yangon Myanmar

ISBN: (纸本)9798331510046

Data mining is an approach to identify the key pattern in Frequent Itemset Mining (FIM) and to find from historical data into very useful data. ECLAT is an aspect of association rule that is applied to determine the relationship connection in item supports. By intersecting the transaction id sets according to the corresponding kth item sets based on depth-first search, ECLAT algorithm computes the support items. During searching best-selling products, ECLAT requires a lot of memory and processing time for large dataset because of the amount of transaction id sets. By merging the K-means clustering algorithm and ECLAT algorithm, the proposed method aims to determine how the K-means clustering algorithm enhances the performance of ECLAT algorithm to generate support items for large dataset. The retail data items from 100000 to 400000 UK consumers were used to retrieve the support items of the most popular selling goods. Firstly, K-means algorithm grouped the same purchased products to cluster the top selling items and then ECLAT algorithm searches the support items from clustering the famous selling products. According to the experimental results, it can be seen that the silhouette score value in this research is 0.586 to indicate a high-quality cluster, the ideal value of k is 8 clusters between 100,000 and 400,000 data items. ECLAT can search the support items based on the clustering of the top eight selling supplies by setting a minimum support value of 0.00001. The proposed method reduces memory usage and execution time to retrieve the support elements for most popular selling items than the ECLAT algorithm for massive dataset. © 2024 IEEE.

关键词： K-means clustering

来源：评论

学校读者我要写书评

暂无评论

Evaluating Public Opinion Through Twitter Sentiment Analysis 2

Evaluating Public Opinion Through Twitter Sentiment Analysis

引用

2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Jadhav, Narendra More, Priyanka Dixit, Akhilesh Sharma, Akshay Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367461

In the digital age, social media platforms like Twitter have become a central forum for public discourse, reflecting diverse opinions on various topics. This paper explores the application of sentiment analysis to Twitter data to extract and quantify these opinions. This work processes and analyzes a large dataset of tweets using machine-learning techniques to identify underlying attitudes and divide them into positive, negative, and neutral categories. The methodology comprises preprocessing such as text normalization and noise removal, sentiment categorization using a model based on Natural Language Processing (NLP) techniques, and data gathering via the Twitter API. The results reveal patterns and trends in public sentiment on key issues, providing insights that can benefit businesses, policymakers, and researchers. This paper discusses the potential real-world applications of this technology in marketing, political science, and public relations. © 2024 IEEE.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Lightweight irregular driving behavior detection algorithm based on star operation 5

Lightweight irregular driving behavior detection algorithm b...

引用

5th International Conference on computer Vision and Data Mining, ICCVDM 2024

作者： Liang, Jiaxin Department of Computer and Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9781510682863

To address the problems of high memory consumption, heavy computational burden, and difficulty deploying existing detection algorithms on edge devices, a lightweight approach for detecting abnormal driving behavior based on an updated YOLOv8 model has been presented. Firstly, the backbone network is replaced with the StarNet network, which has lower computational and memory access requirements. Second, utilizing an enhanced weighted bidirectional feature pyramid network with C2f blocks enhances the model's capability to capture multi-scale features swiftly. Finally, an asymmetric multi-level compression detection head is introduced to reduce the model size further. The experimental findings demonstrate that the suggested enhanced model achieves a 73.2% reduction in parameters, a 60.9% decrease in computational burden, and a 72.8% reduction in model size while retaining the same accuracy as the original YOLOv8 model. This significantly reduces hardware costs, demonstrating excellent lightweight effects. © 2024 SPIE.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Exploring Dual-Module Approaches for Sentiment Analysis in Call Recordings 5

Exploring Dual-Module Approaches for Sentiment Analysis in C...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Dhobale, Nikita Dinkar Elle, Krisha Ramesh Deshmukh, Pratiksha Vilas Nirne, Sakshi Sidram Jarali, Prof. Ashwini International Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350379945

The system entails the development of a sentiment analysis system consisting of two integral modules aimed at analysing audio recordings of calls. The first module predicts sentiment-positive, negative, or neutral-by converting speech to text using speech-to-text APIs and subsequently applying machine learning algorithms including Random Forest, Naive Bayes, SVM, and Logistic Regression. The second module employs audio processing techniques utilising Librosa for feature extraction and Convolutional Neural Networks (CNNs) for emotion recognition. The system facilitates comparisons between the results obtained from both modules for call recordings. Users, starting with system administrators, can choose between two options: browsing for uploading pre-recorded audio files or live recording. In both scenarios, the system executes sentiment analysis and emotion detection, presenting results derived from speech-to-text and audio processing analyses. © 2024 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Leveraging a structure-based and learning-based predictor using various feature groups in bioinformatics (case study: protein-peptide region residue-level interaction) 14

Leveraging a structure-based and learning-based predictor us...

引用

14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Shafiee, Shima Fathi, Abdolhossein Department of Computer Engineering and Information Technology Razi University Kermanshah Iran

ISBN: (纸本)9798331511272

Predicting protein-peptide interactions is crucial for understanding cellular activities, researching protein functions, designing new drugs, studying abnormal cell behavior, and addressing human diseases. Conventional experimental techniques for identifying the residues in protein-peptide interaction regions are labor-intensive and costly. Therefore, determining these binding region residues using computational methods would serve as a valuable and complementary tool. Our research introduces RSPPRI, a computational method that combines a Residual Neural Network and a Support Vector Machine to accurately identify the residues in the binding regions of protein-peptide interactions. To achieve this, we extract various feature groups from protein structures, including evolutionary, physicochemical, and structure-based features. ©2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Leveraging the Potential of Large Language Models

引用

Informatica (Slovenia) 2024年第8期48卷 1-16页

作者： Prasad, Shreya Gupta, Himank Ghosh, Arup Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Computer Science and Information Technology Graceland University LamoniIA United States

This study focuses on enhancing Natural Language Processing (NLP) in generative AI chatbots through the utilization of advanced pre-trained models. We assessed five distinct Large Language Models (LLMs): TRANSFORMER MODEL, FALCON 7B, LAMINI-FLAN-T5-783M, LLAMA-2-7B, and LLAMA-2-13B to identify the most effective one. Our findings revealed that the LLAMA Model excels in comprehending user queries and delivering precise responses during conversations. The article elucidates the methodology employed to evaluate and select various models for our chatbot. Through rigorous testing, we determined that the LLAMA-2-13B model exhibits enhanced response time and accuracy. Additionally, we employed tools such as Facebook Artificial Intelligence Similarity Search (FAISS) and experimented with user interfaces like Streamlit and Chainlit to enhance the chatbot's user-friendliness. The research underscores the significance of selecting the appropriate model for crafting efficient chatbots. Ultimately, the LLAMA-13B model emerged as the standout performer, showcasing superior performance. Benchmark assessments, including HellaSwag and WinoGrande, which gauge common sense reasoning, were employed to evaluate our chatbot's capabilities. The study concludes that LLAMA-based models hold significant promise for the development of innovative and user-friendly chatbots in the future. Povzetek: Študija se osredotoča na izboljšanje obdelave naravnega jezika (NLP) v generativnih AI klepetalnicah z uporabo naprednih vnaprej usposobljenih modelov. Analizirali so pet modelov: TRANSFORMER MODEL, FALCON 7B, LAMINI-FLAN-T5-783M, LLAMA-2-7B in LLAMA-2-13B. Model LLAMA-13B se je izkazal kot najboljši z vrhunskimi rezultati na testih HellaSwag in WinoGrande. Raziskava uporablja orodja, kot je FAISS, in uporabniške vmesnike, kot sta Streamlit in Chainlit za izboljšanje uporabniške izkušnje. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Smart Industrial Machinery Tracking Using Extreme Gradient Boosting and Thermal Mapping 19

Smart Industrial Machinery Tracking Using Extreme Gradient B...

引用

19th Iranian Conference on Intelligent Systems, ICIS 2024

作者： Barzegarzadeh, Marjan Naji, Hamidreza Afzali, Mahbobeh Graduate University of Advanced Technology Department of Computer Engineering and Information Technology Kerman Iran

ISBN: (纸本)9798331507565

This paper introduces a dual-phase methodology aimed at improving the tracking and management of industrial machinery through the application of cutting-edge technologies. The initial phase focuses on the seamless integration of tracking systems with the Extreme gradient boosting algorithm, which facilitates accurate location identification and supports real-time decision-making processes. This integration not only enhances the efficiency of industrial operations but also minimizes the likelihood of human error. The subsequent phase employs a thermal mapping technique to illustrate the movement patterns of machinery. By scrutinizing the thermal maps derived from vehicle location data, it becomes possible to optimize routing, bolster safety measures, and refine maintenance strategies, ultimately leading to heightened operational efficiency and cost reductions. © 2024 IEEE.

关键词： Cost reduction

来源：评论

学校读者我要写书评

暂无评论

Vision Aid For Blind People Using YOLOV8 2

Vision Aid For Blind People Using YOLOV8

引用

2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： More, Priyanka Sangamkar, Satvik Vishwakarma Institute Of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367461

This assistive system for the visually impaired integrates real-time YOLOv8 object detection with distance estimation and text-to-speech conversion, empowering users with enriched environmental awareness. Leveraging robust datasets and architectures, it identifies over 90 everyday objects amidst clutter while concurrently approximating object proximity through trigonometric translations of size metrics. Audio cues enunciate recognized items and distances in real time for accessibility. This combination of precise visual recognition, spatial metrics, and assistive feedback holds promise for enhanced mobility, independence, and safety during navigation for visually impaired individuals. © 2024 IEEE.

关键词： Vision aids

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：