检索结果-内蒙古大学图书馆

8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Zorarpaci, Ezgi Istanbul University Faculty of Computer and Information Technologies Department of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798331531492

Text categorization (TC) is a natural language processing (NLP) task commonly used in text mining. It is defined as the automatic assignment of text to a set of given categories. Ensemble-based methods that unify multiple models effectively improve the prediction performance and result in higher accuracies than a standalone classifier in general. Motivated by this idea, it is proposed to evaluate the performances of the different ensemble classifiers on Turkish TC dataset (i.e., TTC-3600) in this paper. Firstly, OneR attribute evaluator algorithm diminishes the high dimensionality of Turkish text training data. Different combinations of the base classification algorithms are then compared using this reduced data to assess the impact of ensemble learning on Turkish text data. Bayesian network (BN), extra tree (ET), random forest (RF), and multinomial naive bayes (MNB) classification algorithms are used for the base classifiers. bagging, adaBoost, and voting mechanisms are employed to unify these base classifiers in ensemble learning. According to the experimental results, the proposed model achieves a competitive classification accuracy (93.83 %) to the state-of-the-art (SOTA) methods. Moreover, the proposed method has a pretty low runtime that is only 125.8 seconds for TC task. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Dynamically-Tunable Narrowband Color Sensor Compatible with CMOS Technology

引用

IEEE Sensors Journal 2025年第11期25卷 19117-19124页

作者： Asl, Akbar Beheshti Ahmadi, Hodjat Rostami, Ali Faculty of Electrical and Computer Engineering Tabriz Iran Industrial Park of Advanced Technologies SP-EPT Lab. ASEPE Company Tabriz Iran

Color sensors have broad applications in spectroscopy, medical imaging, and CMOS-based cameras. One of the fundamental challenges in this field is implementing a dynamically tunable filter capable of covering the visible spectrum;hence, designing a tunable filter with high spectral resolution and a narrow bandwidth frequency response is essential. In this work, a multilayer color sensor based on Fabry-Pérot resonance is designed, offering the capability for static and dynamic tuning of the transmitted wavelength and the ability to detect different colors in an integrated device, including a filter and detector. The filter comprises four parts: blue, green, yellow-orange, and red. The detector is a simple PN photodiode. The dynamic adjustment is performed via the voltage applied to the filter. In addition to the dynamic tunability, a key characteristic of this structure is its bandwidth, which remains consistently below 9, 8.5, 8, and 11.5 nm for blue, green, yellow-orange, and red regions, respectively. Notably, the materials used in this structure have been selected to be compatible with CMOS technology. Another feature of this sensor is its 50 nm spectral shift for each specified spectrum, achieved with a 15-volt bias. Furthermore, this device presents minuscule crosstalk (below 5%) compared to other devices. © 2001-2012 IEEE.

关键词： CMOS integrated circuits

来源：评论

学校读者我要写书评

暂无评论

The Security of Using Large Language Models:A Survey With Emphasis on ChatGPT

引用

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 1-26页

作者： Wei Zhou Xiaogang Zhu Qing-Long Han Lin Li Xiao Chen Sheng Wen Yang Xiang the School of Science Computing and Engineering Technologies Swinburne University of Technology IEEE the School of Computer and Mathematical Sciences the University of Adelaide Adelaide the Faculty of Science and Engineering Southern Cross University the School of Information and Physical Sciences the University of Newcastle

ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.

关键词： Artificial intelligence (AI) ChatGPT large language models (LLMs) security

来源：评论

学校读者我要写书评

暂无评论

Improving Brain Tumor Classification with Deep Learning Using Synthetic Data

引用

computers, Materials & Continua 2023年第3期74卷 5049-5067页

作者： Muhammed Mutlu Yapici Rukiye Karakis Kali Gurkahraman Elmadag Vocational School Department of Computer TechnologiesAnkara UniversityAnkaraTurkey Faculty of Technology Department of Software EngineeringSivas Cumhuriyet UniversitySivas58140Turkey Faculty of Engineering Department of Computer EngineeringSivas Cumhuriyet UniversitySivas58140Turkey

Deep learning(DL)techniques,which do not need complex preprocessing and feature analysis,are used in many areas of medicine and achieve promising *** the other hand,in medical studies,a limited dataset decreases the abstraction ability of the DL *** this context,we aimed to produce synthetic brain images including three tumor types(glioma,meningioma,and pituitary),unlike traditional data augmentation methods,and classify them with *** study proposes a tumor classification model consisting of a Dense Convolutional Network(DenseNet121)-based DL model to prevent forgetting problems in deep networks and delay information flow between *** comparing models trained on two different datasets,we demonstrated the effect of synthetic images generated by Cycle Generative Adversarial Network(CycleGAN)on the generalization of *** model is trained only on the original dataset,while the other is trained on the combined dataset of synthetic and original *** data generated by CycleGAN improved the best accuracy values for glioma,meningioma,and pituitary tumor classes from 0.9633,0.9569,and 0.9904 to 0.9968,0.9920,and 0.9952,*** developed model using synthetic data obtained a higher accuracy value than the related studies in the ***,except for pixel-level and affine transform data augmentation,synthetic data has been generated in the figshare brain dataset for the first time.

关键词： Brain tumor classification deep learning cycle generative adversarial network data augmentation

来源：评论

学校读者我要写书评

暂无评论

Fractal Measurement of Images Human Brain from MRI

Fractal Measurement of Images Human Brain from MRI

引用

2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Anarova, Shahzoda Jabbarov, Jamoliddin Uralova, Iroda Tashkent University of Information Technologies Department of Convergence of digital technologies Computer Engineering Faculty Tashkent Uzbekistan Department of Computer science and technology Intelligent systems and computer technologies Faculty Samarkand State University Samarkand Uzbekistan

ISBN: (纸本)9798400716928

This article is devoted to the determination of the fractal size of the damaged part of the human brain on the basis of images obtained from MRI (magnetic resonance imaging). There are various mathematical methods for determining the size of fractal structures, this article uses two variants of the cell counting method and describes the analysis of errors in determining the fractal size of the damaged part of the human brain. The article shows that the damaged part of the human brain has a fractal structure and that it has a fractal dimension. Fractal measurement has also been used to determine the size of the damaged part of the human brain, unlike common methods. In determining the fractal scale, cases of changes in human body organs were not taken into account. In the article, the determination of the size of the damaged part of the human brain is studied on the basis of mathematical formulas. Two different variants of the special cell counting method were used to calculate the fractal measurements, as well as the corresponding number of experimental results. In addition, these measurements were used to assess the extent to which patients suffered brain damage and to provide information on the practical application of these fractal measurements. © 2024 ACM.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

RUSAS: Roman Urdu Sentiment Analysis System

引用

computers, Materials & Continua 2024年第4期79卷 1463-1480页

作者： Kazim Jawad Muhammad Ahmad Majdah Alvi Muhammad Bux Alvi Faculty of Computer Science and Engineering Frankfurt University of Applied SciencesFrankfurt am Main60318Germany Technical Writer and Researcher Proteus Technologies LLCIslamabad04405Pakistan Faculty of Engineering The Islamia University of BahawalpurBahawalpur63100Pakistan

Sentiment analysis, the meta field of Natural Language Processing (NLP), attempts to analyze and identify thesentiments in the opinionated text data. People share their judgments, reactions, and feedback on the internetusing various languages. Urdu is one of them, and it is frequently used worldwide. Urdu-speaking people prefer tocommunicate on social media in Roman Urdu (RU), an English scripting style with the Urdu language *** have developed versatile lexical resources for features-rich comprehensive languages, but limitedlinguistic resources are available to facilitate the sentiment classification of Roman Urdu. This effort encompassesextracting subjective expressions in Roman Urdu and determining the implied opinionated text polarity. Theprimary sources of the dataset are Daraz (an e-commerce platform), Google Maps, and the manual effort. Thecontributions of this study include a Bilingual Roman Urdu Language Detector (BRULD) and a Roman UrduSpelling Checker (RUSC). These integrated modules accept the user input, detect the text language, correct thespellings, categorize the sentiments, and return the input sentence’s orientation with a sentiment intensity *** developed system gains strength with each input experience gradually. The results show that the languagedetector gives an accuracy of 97.1% on a close domain dataset, with an overall sentiment classification accuracy of94.3%.

关键词： Roman Urdu sentiment analysis Roman Urdu language detector Roman Urdu spelling checker flask

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Dynamic Area Coverage Based on Reinforcement Learning with Connected Agents

引用

computer Systems Science & engineering 2023年第4期45卷 215-230页

作者： Fatih Aydemir Aydin Cetin STM Defence Technologies Engineering and Trade.Inc. Ankara06560Turkey Department of Computer Engineering Faculty of TechnologyGazi UniversityAnkara06500Turkey

Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making *** behavior of a group of UAVs in an unknown environment is another hard problem to be *** this paper,we propose a method for decentralized execution of multi-UAVs for dynamic area coverage *** proposed decentralized decision-making dynamic area coverage(DDMDAC)method utilizes reinforcement learning(RL)where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable *** agents increase their global observations by gathering information about the environment by connecting with other *** connectivity provides a consensus for the decision-making process,while each agent takes *** each step,agents acquire all reachable agents’states,determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area,*** method was tested in a multi-agent actor-critic simulation *** the study,it has been considered that each UAV has a certain communication distance as in real *** results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.

关键词： Dynamic environments multi-agent reinforcement learning dynamic area coverage

来源：评论

学校读者我要写书评

暂无评论

Training neuro-fuzzy using flower pollination algorithm to predict number of COVID-19 cases: situation analysis for twenty countries

引用

Neural Computing and Applications 2024年第26期36卷 16365-16393页

作者： Baştemur Kaya, Ceren Kaya, Ebubekir Department of Computer Technologies Nevsehir Vocational School Nevsehir Haci Bektas Veli University Nevşehir Turkey Department of Computer Engineering Engineering Architecture Faculty Nevsehir Haci Bektas Veli University Nevşehir Turkey

Predicting the number of COVID-19 cases offers a reflection of the future, and it is important for the implementation of preventive measures. The numbers of COVID-19 cases are constantly changing on a daily. Adaptive methods are needed for an effective estimation instead of traditional methods. In this study, a novel method based on neuro-fuzzy and FPA is proposed to estimate the number of COVID-19 cases. The antecedent and conclusion parameters of the neuro-fuzzy model are determined by using FPA. In other words, neuro-fuzzy training is carried out with FPA. The number of COVID-19 cases belonging to twenty countries including USA, India, Brazil, Russian, France, UK, Italy, Spain, Argentina, Germany, Colombia, Mexico, Poland, Turkey, Iran, Peru, Ukraine, South Africa, the Netherlands and Indonesia is estimated. Time series is created using the number of COVID-19 cases. Daily, weekly and monthly estimates are realized by utilizing these time series. MSE is used as the error metric. Although it varies according to the example and problem type, the best training error values between 0.000398027 and 0.0286562 are obtained. These best test error values are between 0.0005607 and 0.409867. The best training and test error values are 0.000398027 and 0.0005607, respectively. In addition to FPA, the number of cases is also predicted with the algorithms such as particle swarm optimization, harmony search, bee algorithm, differential evolution and their performances are compared. Success score and ranking are created for all algorithms. The scores of FPA for the daily, weekly and monthly forecast are 71, 77 and 62, respectively. These scores have shown that neuro-fuzzy training based on FPA is successful than other meta-heuristic algorithms for all three prediction types in the short- and medium-term estimation of COVID-19 case numbers. © The Author(s) 2024.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Optimizing Image Retrieval in Cloud Servers with TN-AGW: A Secure and Efficient Approach

引用

Journal of The Institution of Engineers (India): Series B 2025年第2期106卷 459-473页

作者： Ponnuviji, N.P. Nirmala, G. Kokila, M. L. Sworna Priyadharshini, S. Indra Department of Computer Science and Engineering RMK College of Engineering and Technology Puduvoyal Thiruvallur India Department of Computer Science and Engineering RMD Engineering College Chennai India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nādu Kattankulathur Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

The increasing use of cloud-based image storage and retrieval systems has made ensuring security and efficiency crucial. The security enhancement of image retrieval and image archival in cloud computing has received considerable attention in transmitting data and ensuring data confidentiality among cloud servers and users. Various traditional image retrieval techniques regarding security have developed in recent years but they do not apply to large-scale environments. This paper introduces a new approach called Triple network-based adaptive grey wolf (TN-AGW) to address these challenges. The TN-AGW framework combines the adaptability of the Grey Wolf Optimization (GWO) algorithm with the resilience of Triple Network (TN) to enhance image retrieval in cloud servers while maintaining robust security measures. By using adaptive mechanisms, TN-AGW dynamically adjusts its parameters to improve the efficiency of image retrieval processes, reducing latency and utilization of resources. However, the image retrieval process is efficiently performed by a triple network and the parameters employed in the network are optimized by Adaptive Grey Wolf (AGW) optimization. Imputation of missing values, Min–Max normalization, and Z-score standardization processes are used to preprocess the images. The image extraction process is undertaken by a modified convolutional neural network (MCNN) approach. Moreover, input images are taken from datasets such as the Landsat 8 dataset and the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset is employed for image retrieval. Further, the performance such as accuracy, precision, recall, specificity, F1-score, and false alarm rate (FAR) is evaluated, the value of accuracy reaches 98.1%, the precision of 97.2%, recall of 96.1%, and specificity of 917.2% respectively. Also, the convergence speed is enhanced in this TN-AGW approach. Therefore, the proposed TN-AGW approach achieves greater efficiency in image retrieving than other existing

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

Multispectral point cloud superpoint segmentation

引用

Science China(Technological Sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer Technologies Application Kunming 650500China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral Information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

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：