检索结果-内蒙古大学图书馆

2025 International Conference on Computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Thiyagarajan, Gomathi Swathi, Y. Cmr Institute of Technology Department of Computer Applications Bengaluru India Gopalan College of Engineering and Management Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331538538

This paper explores into an indepth analysis of consumer behavior on an e-commerce platform, extending the study period to include November 2019 through February 2020. Looking at user interactions that come under the categories of views, carts, purchases, and removals from cart along with process discovery visualizations will help identify complex patterns of engagement, measure the impact of interface changes and quantify marketing intervention's successes. This research uses sophisticated data analytics through process mining to provide recommendations for improving the e-commerce journey through increased user satisfaction and better conversion rates. © 2025 IEEE.

关键词： Marketplaces

来源：评论

学校读者我要写书评

暂无评论

Design of a Lightweight Compressed Video Stream-Based Patient Activity Monitoring System

引用

computers, Materials & Continua 2024年第1期78卷 1253-1274页

作者： Sangeeta Yadav Preeti Gulia Nasib Singh Gill Piyush Kumar Shukla Arfat Ahmad Khan Sultan Alharby Ahmed Alhussen Mohd Anul Haq Department of Computer Science&Applications Maharshi Dayanand UniversityRohtak124001India University Institute of Technology Rajiv Gandhi Proudyogiki VishwavidyalayaBhopal462033India Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia

Inpatient falls from beds in hospitals are a common *** falls may result in severe *** problem can be addressed by continuous monitoring of patients using *** advancements in deep learning-based video analytics have made this task of fall detection more effective and *** with fall detection,monitoring of different activities of the patients is also of significant concern to assess the improvement in their *** computation-intensive models are required to monitor every action of the patient *** requirement limits the applicability of such ***,to keep the model lightweight,the already designed fall detection networks can be extended to monitor the general activities of the patients along with the fall *** by the same notion,we propose a novel,lightweight,and efficient patient activity monitoring system that broadly classifies the patients’activities into fall,activity,and rest classes based on their *** whole network comprises three sub-networks,namely a Convolutional Neural Networks(CNN)based video compression network,a Lightweight Pose Network(LPN)and a Residual Network(ResNet)Mixer block-based activity recognition *** compression network compresses the video streams using deep learning networks for efficient storage and retrieval;after that,LPN estimates human ***,the activity recognition network classifies the patients’activities based on their *** proposed system shows an overall accuracy of approx.99.7% over a standard dataset with 99.63% fall detection accuracy and efficiently monitors different events,which may help monitor the falls and improve the inpatients’health.

关键词： Fall detection activity recognition human pose estimation accuracy

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Detection using Optimized Stochastic Gradient Descent Function

Brain Tumor Detection using Optimized Stochastic Gradient De...

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Mishra, Annu Chaturvedi, Ravi Prakash Sharma, Hirdesh Kumar, Prashant Asthana, Sameer Parashar, Mayank Sharda School of Engineeringand Technology Department of Computer Science and Engineering Greater Noida India Sharda School of Engineeringand Technology Department of Computer Science and Applications Greater Noida India JEMTEC Department of Computer Science and Engineering Greater Noida India ITS Engineering College Department of Computer Science and Engineering Greater Noida India GNIOT Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350378092

The learning rate of a CNN determines the efficiency of the neural network. In brain tumor detection, the learning rate and the optimization function plays a key role in deciding the final output. The Optimized Stochastic Gradient Descent (OSGD) optimizer giver better result in terms of Accuracy, Recall and other determining factors. We have also compared the results obtained with other optimizers and it could be clearly stated that our proposed model. The OSGD optimizer controls the maxima and minima, and move the near optimum solution buy controlling the learning rate. So via this method we can control our right *** we detect our object in les error. © 2024 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Career Prospect Prediction System for Non-computer Stream Students in Software Companies 1st

An Enhanced Career Prospect Prediction System for Non-comput...

引用

1st International Conference on Computational Intelligence for engineering and Management applications, CIEMA 2022

作者： Abraham, Biku Ambili, P.S. Department of Computer Applications Saintgits College of Engineering Kottayam India School of Computer Science and Applications REVA University Bangalore India

ISBN: (纸本)9789811984921

The stakeholders of the present education system have a key focus on the chances of on-campus employability of their wards. Since software companies play prominent role as campus recruiters, there is a low demand for the traditional engineering branches. The need to enhance skills for software related employment is a challenge to the private sector professional institutions for the existence of non-computer streams in this scenario. In this study, the authors being academic experts in the similar field, attempt to support institutions, students, curriculum designers, and the faculty by providing insight to better employment possibility in campus. Data set for the study is from the same institution for which the placement prediction was completed. The methodology models the problem as a sequential event prediction problem and employs deep learning techniques. The system extracts data from data set with 19 attributes. The results indicate that this predictive approach provides enhancement methods by which a non-computer stream student can ensure full-time employment in software related jobs through in-campus selection. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

IAOMDR: Improved Aquila Optimized Hybrid deep learning Model for Classification of Diabetic Retinopathy 2

IAOMDR: Improved Aquila Optimized Hybrid deep learning Model...

引用

2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Saju, Binju Barwal, Sahil Asha, V. Kumar, Shubham Tressa, Neethu Nikhil, T. Adi Shankara Institute of Engineering & Technology Department of Computer Science-AI Engineering Kalady India New Horizon College of Engineering Department of Master of Computer Applications Bengaluru India

ISBN: (纸本)9798350328202

One of the scariest illnesses that causes irreversible blindness is Diabetic Retinopathy (DR). As a result, early exposure to Diabetic Retinopathy can help to preserve vision. The study proposes a hybrid model to classify Diabetic Retinopathy images. Initially, pre-processing of the photographs includes resizing them. Grey scale translation and noise removing using a combination of Weiner filter and Median filter. Further, images are enhanced using Gaussian Mixture based histogram equalization. Features of the images are extracted using Dense Convolutional neural network. An optimized ResNet101 model with improved Aquila optimization is used for classification. Performance of the models is as opposed to other studies in literature. The proposed model has acquired F1 score of 98.98%, accuracy of 99.2%, sensitivity of 98.9%, specificity of 99.1%, and precision of 99%. © 2024 IEEE.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

Copy Move Forgery Detection Using Novel Quadsort Moth Flame Light Gradient Boosting Machine

引用

computer Systems science & engineering 2023年第5期45卷 1577-1593页

作者： R.Dhanya R.Kalaiselvi Department of Computer Applications Noorul Islam Centre for Higher EducationNagercoil629180India Department of Computer Science Engineering Noorul Islam Centre for Higher EducationNagercoil629180India

A severe problem in modern information systems is Digital media tampering along with fake *** though there is an enhancement in image development,image forgery,either by the photographer or via image manipulations,is also done in *** researches have been concentrated on how to identify such manipulated media or information manually along with automatically;thus conquering the complicated forgery methodologies with effortlessly obtainable technologically enhanced ***,high complexity affects the developed ***,it is complicated to resolve the issue of the speed-accuracy *** tackling these challenges,this article put forward a quick and effective Copy-Move Forgery Detection(CMFD)system utilizing a novel Quad-sort Moth Flame(QMF)Light Gradient Boosting Machine(QMF-Light GBM).Utilizing Borel Transform(BT)-based Wiener Filter(BWF)and resizing,the input images are initially pre-processed by eliminating the noise in the proposed *** that,by utilizing the Orientation Preserving Simple Linear Iterative Clustering(OPSLIC),the pre-processed images,partitioned into a number of grids,are ***,as of the segmented images,the significant features are extracted along with the feature’s distance is calculated and matched with the input ***,utilizing the Union Topological Measure of Pattern Diversity(UTMOPD)method,the false positive matches that took place throughout the matching process are *** that,utilizing the QMF-Light GBM visualization,the visualization of forged in conjunction with non-forged images is *** extensive experiments revealed that concerning detection accuracy,the proposed system could be extremely precise when contrasted to some top-notch approaches.

关键词： Borel transform based wiener filter(BWF) orientation preserving simple linear iterative clustering(OPSLIC) keypoint features block features outlier detection

来源：评论

学校读者我要写书评

暂无评论

Improved Metaheuristic Based Failure Prediction with Migration Optimization in Cloud Environment

引用

computer Systems science & engineering 2023年第5期45卷 1641-1654页

作者： K.Karthikeyan Liyakathunisa Eman Aljohani Thavavel Vaiyapuri Department of Computer Applications Anna UniversityRegional CampusMaduraiMaduraiIndia Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinahSaudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Cloud data centers consume high volume of energy for processing and switching the servers among different *** Machine(VM)migration enhances the performance of cloud servers in terms of energy efficiency,internal failures and *** the other end,energy utilization can be minimized by decreasing the number of active,underutilized sources which conversely reduces the dependability of the *** VM migration process,the VMs are migrated from underutilized physical resources to other resources to minimize energy utilization and optimize the *** this view,the current study develops an Improved Metaheuristic Based Failure Prediction with Virtual Machine Migration Optimization(IMFP-VMMO)model in cloud *** major intention of the proposed IMFP-VMMO model is to reduce energy utilization with maximum performance in terms of failure *** accomplish this,IMFPVMMO model employs Gradient Boosting Decision Tree(GBDT)classification model at initial stage for effectual prediction of VM *** the same time,VMs are optimally migrated using Quasi-Oppositional Artificial Fish Swarm Algorithm(QO-AFSA)which in turn reduces the energy *** performance of the proposed IMFP-VMMO technique was validated and the results established the enhanced performance of the proposed *** comparative study outcomes confirmed the better performance of the proposed IMFP-VMMO model over recent approaches.

关键词： Cloud computing energy efficiency virtual machine migration failure prediction energy optimization metaheuristics

来源：评论

学校读者我要写书评

暂无评论

Cumulative Summary List Driven Lightweight Frequent Closed High Utility Itemset Mining 2

Cumulative Summary List Driven Lightweight Frequent Closed H...

引用

2nd International Conference for Innovation in Technology, INOCON 2023

作者： Siva, S. Chaudhari, Shilpa REVA University School of Computer Science and Applications Bangalore India Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350320923

Pattern mining has always been a dominant approach in data mining to identify the object(s) of interest from a humongous large data space to make real-time decisions. In sync with diverse business intelligence or other enterprise demands, pattern mining methods have gained wide-spread attention to serve purposes like high-utility itemset identification, segmentation and top-(itemsets) recommendation. In this paper, a robust cumulative summary list-structure driven lightweight frequent closed high-utility itemsets mining model (CSLFC-HUIM) is proposed that uses an improved cumulative summary list structure (CULS) to ensure optimal set of candidate itemsets in search space. Unlike classical support value driven strict-thresholding, CSLFCHUIM applied lift-score as minimum threshold called cumulative support/utility threshold to prune the search space. The strategic amalgamation of cumulative support value, utility threshold with CULS and cumulative summary list structure (CSLS) concept guarantee optimal set of itemsets in nested-list structure. It reduces unwanted database-scanning, execution-time and memory exhaustion, which makes it a potential solution for different pattern mining and business intelligence tasks. © 2023 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Enhancing Medical Image Segmentation with Recurrent Neural Network Architectures 2

Enhancing Medical Image Segmentation with Recurrent Neural N...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Masson, Palak Sharma, Deepak Yadav, Kanchan Sethi, Tarun Raj Kumar Goel Institute of Technology Department of Computer Science & Engineering UP Ghaziabad India Srm Institute of Science and Technology Department of Computer Applications UP Modinagar India Gla University Department of Mechanical Engineering UP Mathura India Iamr Department of Computer Applications UP Ghaziabad India

ISBN: (纸本)9798350371055

Scientific imaging is a swiftly evolving and developing vicinity of healthcare. Greater accurate segmentation of clinical images is paramount for correct diagnosis. Recent breakthroughs in profound mastering studies have allowed researchers to faucet into a powerful but unstructured information form - images. With the usage of recurrent neural network architectures (RNNs), researchers are exploring the capacity of this shape of facts to acquire better consequences from scientific photograph segmentation. RNNs are regarded for their flexibility in encoding temporal relationships and processing established statistics. In medical image segmentation, this flexibility aids in recognizing complicated styles in photographs and helps the model to localize features inside the image better. Furthermore, the networks can run on images of various sizes, ensuring that models can handle photos created using unique imaging modalities. Additionally, RNNs can examine large annotated datasets and, consequently, help supply meaningful segmentation outcomes. Recent advances in using RNNs for medical photo segmentation have shown promising effects. RNNs have been used to phase colon anatomy, mind tumors, and lymph nodes. U-internet-primarily based segmentation fashions that include RNNs and feature-achieved high segmentation accuracy for medical photograph segmentation responsibilities have also evolved. Within destiny, RNN-based total models will remain superior and could be implemented in various medical imaging segmentation tasks. As such, RNNs will make scientific imaging segmentation extra green and accurate, allowing faster and more accurate analysis and treatment. © 2024 IEEE.

关键词： Achieved Recognizing Relationships Segmentation

来源：评论

学校读者我要写书评

暂无评论

Webcam-Based OCR System with Text-to-Speech Conversion 5

Webcam-Based OCR System with Text-to-Speech Conversion

引用

5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Nair, Rekha R Babu, Tina Kishore, S. Poornima, J. Sambasivudu, Madduru Bhargavi, Manchikalapudi Alliance School of Advanced Computing Alliance University Department of Computer Science and Engineering Bengaluru India Department of Computer Applications Mangalore India Brindavan College of Engineering Department of Information Science and Engineering Bengaluru India Malla Reddy College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331530013

The project develops an OCR system that converts webcam-captured text to speech, featuring user registration for personalized experiences. Key components include image capture via webcam, text extraction using OCR, database storage, and text-to-speech conversion. The system employs Python, OpenCV for image processing, Tesseract for OCR, and Google Text-to-Speech for audio output. Main objectives are to streamline text digitization and assist visually impaired users. The modular design allows for future enhancements like language translation. Comprehensive testing ensures reliability and effectiveness. The system demonstrates an efficient solution for converting printed text to digital and audio formats, with applications in document digitization, education, and accessibility services. It reduces manual effort in text digitization and improves access to written information for visually impaired individuals, showcasing potential across various fields. © 2024 IEEE.

关键词： Optical character recognition

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：