检索结果-内蒙古大学图书馆

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Siddhant Gautam Angqi Li Saiprasad Ravishankar Dept. of Computational Mathematics Science and Engineering Michigan State University East Lansing MI USA Dept. of Biomedical Engineering Michigan State University East Lansing MI USA

There has been much recent interest in adapting undersampled trajectories in MRI based on training data. In this work, we propose a novel patient-adaptive MRI sampling algorithm based on grouping scans within a training set. Scan-adaptive sampling patterns are optimized together with an image reconstruction network for the training scans. The training optimization alternates between determining the best sampling pattern for each scan (based on a greedy search or iterative coordinate descent (ICD)) and training a reconstructor across the dataset. The eventual scan-adaptive sampling patterns on the training set are used as labels to predict sampling design using nearest neighbor search at test time. The proposed algorithm is applied to the fastMRI knee multicoil dataset and demonstrates improved performance over several baselines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advancements in EEG-Based Emotion and Consciousness Recognition: Techniques, Challenges, and Innovations

Advancements in EEG-Based Emotion and Consciousness Recognit...

引用

Innovations in Communications, Electrical and Computer engineering (ICICEC), International Conference on

作者： Ranjana B Jadekar Poornima B Gowramma B H Puneeth S P Dept. of Computer Science and Engineering Data Science Bapuji Institute of Engineering and Technology Visvesvaraya Technological University Belavavi Karnataka India Dept. of Information Science and Engineering Bapuji Institute of Engineering and Technology Visvesvaraya Technological University Belavavi Karnataka India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376524

This study delves into the application of Electroencephalogram (EEG)-based techniques for emotion and consciousness recognition, focusing on disorders of consciousness (DOC). By evaluating existing approaches in terms of techniques, methodologies, and accuracies, the research highlights the efficacy of both machine learning and deep learning models. The key challenges were identified such as noise removal due to artifacts and variability in patient responses. The findings underscore the potential of advanced computational methods in enhancing the reliability and precision of EEG-based diagnostic tools, paving the way for better clinical interventions and deeper understanding of human emotions. Also, the findings show that using deep learning, the current works have achieved better results for identification of emotion.

关键词： Deep learning Technological innovation Emotion recognition Accuracy computational modeling Noise Noise reduction Brain modeling Electroencephalography Reliability

来源：评论

学校读者我要写书评

暂无评论

DeepCensored: Deep-Learning Based Probabilistic Forecasting Framework for Censored data

DeepCensored: Deep-Learning Based Probabilistic Forecasting ...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Jiahao Tian Michael D. Porter School of Data Science University of Virginia Charlottesville VA USA Dept. of Systems and Information Engineering School of Data Science University of Virginia Charlottesville VA USA

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

Accurate time series forecasting is critical in various fields, including resource allocation and crime prevention. While traditional approaches often focus on continuous data, count data forecasting, especially with partially observed (censored) data, remains challenging. This paper introduces DeepCensored, a novel deep learning-based framework that combines the Expectation-Maximization (EM) algorithm with deep neural networks to deliver robust probabilistic forecasts. DeepCensored naturally handles interval-censored event data, where exact event times are unknown but fall within a specific interval. Through extensive simulations and real-world crime data analysis, our method significantly outperforms traditional forecasting approaches, reducing the Mean Absolute Error (MAE) by 50% and better detection of emerging crime trends. These results highlight DeepCensored's potential to provide actionable insights for law enforcement and public safety by predicting crime intensity and enabling resource-efficient policing strategies.

关键词： Time series analysis Predictive models Probabilistic logic Market research data models Time measurement Public security Resource management Forecasting Synthetic data

来源：评论

学校读者我要写书评

暂无评论

The Utilization of Google Cloud in the Healthcare Industry

The Utilization of Google Cloud in the Healthcare Industry

引用

Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： Rishikesh Kapse Palash Gourshettiwar Dept. of Artificial Intelligence and Data Science Faculty of Engineering and Technology DMIHER (DU) Sawangi(M) Wardha Maharashtra Dept. of Computer Science And Medical Engineering Faculty of Engineering and Technology DMIHER (DU) Sawangi(M) Wardha Maharashtra

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

This essay's primary focus is on Google Cloud's use in healthcare and how it affects data management, teamwork, and cost-effectiveness. With a focus on Google Cloud, which improves the processing, storing, and accessibility of medical data, the study examines the trends, advantages, and persistent challenges that come with the increasing usage of cloud computing technology. These consist of remote patient monitoring, “artificial intelligence,” and “machine learning” applications in diagnostics, diagnostics, and personalized medicine. data privacy, security issues, and concerns with the HIPAA incident are among the problems that are discussed along with all the significant elements that could facilitate the cloud migration of healthcare.

关键词： Industries Cloud computing data privacy Technological innovation Medical services Machine learning Teamwork Security Predictive analytics Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Indoor Real-Time Location System for Efficient Location Tracking Using IoT

Indoor Real-Time Location System for Efficient Location Trac...

引用

2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022

作者： Verma, Sunny Raj, Tej Joshi, Kapil Raturi, Preeti Anandaram, Harishchander Gupta, Ashulekha Dev Bhoomi Uttarakhand University Dept. of Electronics & Communication Engineering Dehradun India Uttaranchal University Dept. of Computer Science & Engineering Dehradun India Tula's Institute of Technology Dept. of Computer Science & Engineering Dehradun India Amrita Vishwa Vidyapeetham Centre for Excellence in Computational Engineering and Networking Tamil Nadu Coimbatore India Graphic Era University Dept. of Management Studies Dehradun India

ISBN: (数字)9781665479882

ISBN: (纸本)9781509050017

Researchers have broadened the focus of RFID technology development because to the growing need for low-cost edge devices to bridge the physical-digital gap. In addition to item identification, researchers have explored the use of RFID tags for low-power wireless sensing, localization, and activity inference. A security system utilized today is not powerful enough to provide a real-time alert after identifying a problem. Movement detection is a technology for detecting a change in the environment relative to an object. Sensor-based applications can be used to watch activity and receive alerts when movement is detected, which solves the issue and saves time and money. RFID technology is used to track the location of people or things in an interior setting in real time. A reader and several tags, each of which can house a number of sensors, make up an RFID system. In this research, we present the iLocate framework for the IoT, a recently developed real-time locating framework using dynamic RFID for resource the board in indoor settings. iLocate used ubidots to assist with a broad range RFID organization. Our exploratory findings and the actual project have both shown the prevalence. Location tracking indoors will be more effective using this iLocate framework. © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Predictive Modeling of Fire Hazard: Integrating Environmental Factors with Machine Learning

Predictive Modeling of Fire Hazard: Integrating Environmenta...

引用

International Conference on Electrical, Computer and Communication engineering (ECCE)

作者： Tanjim Taharat Aurpa Samiha Maisha Jeba Khaza Minhaz Bin Monib Maherun Nessa Ela Md Shoaib Ahmed Md Musfique Anwar Dept. of Data Science and Engineering Bangabandhu Sheikh Mujibur Rahman Digital University Gazipur Bangladesh Dept. of Computer Science and Engineering International University of Business Agriculture and Technology Bangladesh Boise State University Boise Idaho USA Dept. of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

In today’s fast-paced world, where technology is advancing rapidly, the tragic loss of lives due to fire accidents is not only heart-wrenching but also poses a significant risk to public safety. Early prediction of such risks can play a crucial role in educating people about fire hazards, enabling them to be better prepared in case they find themselves in such unfortunate circumstances. Our study employed various machine learning (ML) techniques and evaluated their effectiveness by analyzing different factors. These factors are derived from the diverse living conditions in Bangladesh and were gathered through surveys. To refine and identify the critical features for classification, we utilized feature selection methods like ANOVA-f and the chi-square test. Our approaches have achieved a success rate of up to 97.98%.

关键词： Surveys Accuracy Feature extraction Hazards Encoding Vectors Public security Bayes methods Analysis of variance Random forests

来源：评论

学校读者我要写书评

暂无评论

Analytics, have some humility: a statistical view of fourth-down decision making

arXiv

引用

arXiv 2023年

作者： Brill, Ryan S. Yurko, Ronald Wyner, Abraham J. Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania United States Dept. of Statistics and Data Science Carnegie Mellon University United States Dept. of Statistics and Data Science The Wharton School University of Pennsylvania United States

The standard mathematical approach to fourth-down decision making in American football is to make the decision that maximizes estimated win probability. Win probability estimates arise from machine learning models fit from historical data. These models attempt to capture a nuanced relationship between a noisy binary outcome variable and game-state variables replete with interactions and non-linearities from a finite dataset of just a few thousand games. Thus, it is imperative to knit uncertainty quantification into the fourth-down decision procedure;we do so using bootstrapping. We find that uncertainty in the estimated optimal fourth-down decision is far greater than that currently expressed by sports analysts in popular sports media. Copyright © 2023, The Authors. All rights reserved.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Boothless Toll Collection System

Boothless Toll Collection System

引用

International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)

作者： Swagata Sarkar Selvabharathi M Sarveswaran D Arun Raja M Aswin Raju Dept. of Artificial Intelligence and Data Science Sri Sairam Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

As a developing country, it is critical that we prioritize the construction and improvement of our road infrastructure in order to stimulate economic growth and promote easier logistics operations. However, the current toll collection system is hampered by difficulties such as overcharging and traffic congestion, reducing its effectiveness. To solve these issues, we propose implementing an advanced toll collection system that includes GPS technology, an ANPR camera, and a variety of machine learning algorithms. This new method will transform toll collecting by properly calculating toll charges based on the actual distance traveled by vehicles on the highway, removing the need for drivers to stop at toll booths. The system uses GPS technology to precisely compute the distance traveled by each car, while ANPR cameras guarantee the journey’s validity. As a result, vehicles will only be paid for what distance they have traveled, reducing overcharging concerns and congestion at toll gates. Our major goal is to create a smooth and efficient tolling mechanism that overcomes the limitations of traditional tollgate systems. We hope to improve the toll collection process, shorten wait times, and reduce the consumption of fuel associated with long lines at toll booths by utilizing cutting-edge technologies. By applying this innovative strategy, we hope to improve not only toll collecting efficiency but also commuters' overall driving experience.

关键词： Machine learning algorithms Roads Transforms Pricing Logic gates Cameras Traffic congestion Global Positioning System Vehicles Logistics

来源：评论

学校读者我要写书评

暂无评论

An Al Powered Exam Proctoring: Comprehensive Monitoring for Integrity

An Al Powered Exam Proctoring: Comprehensive Monitoring for ...

引用

Knowledge engineering and Communication Systems (ICKECS), International Conference on

作者： Dhruv Mewada Shlok Gaikwad Bhavika Gharat Priyanshu Kamble Dept. of Artificial Intelligence&Data science Vidyavardhini’s College of Engineering and Technology Mumbai India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

In recent times, remote learning has experienced significant growth, yet the challenge of conducting academic examinations in a secure manner persists. Various approaches have been adopted by universities, such as collecting assignments susceptible to plagiarism or implementing remote proctoring with manual supervision. As our current lifestyle appears to be transitioning towards a new normal, it becomes imperative to explore effective solutions. This paper introduces a proposed remedy: the development of an AI-based integrated system designed to prevent cheating during examinations. The system not only detects fraudulent activities but also records evidence, ensuring both security and cost-effectiveness.

关键词： Knowledge engineering Technological innovation Distance learning Face recognition Plagiarism Speech recognition Manuals

来源：评论

学校读者我要写书评

暂无评论

Hyperparameter Tuning of SVM Using Metaheuristics: An Empirical Analysis

Hyperparameter Tuning of SVM Using Metaheuristics: An Empiri...

引用

Wireless Africa Conference (WAC)

作者： Sunday O. Oladejo Lateef A. Akinyemi Stephen O. Ekwe Taiwo G. Omomule Oluwaseyi P. Babalola School for Data Science and Computational Thinking Stellenbosch University South Africa Centre for Augmented Intelligence and Data Science University of South Africa South Africa Dept. of Electrical Electronic and Comp. Engineering Cape Peninsula University of Technology South Africa Dept of Mathematics and Statistics University of Guelph Ontario Canada

ISBN: (数字)9798331517588

ISBN: (纸本)9798331517595

The Support Vector Machine (SVM) performance is highly dependent on the selection of optimal hyperparameterse Conventional optimisation methods, including grid search, gradient descent, randomized search, and various experimental approaches, have been extensively utilized in the literature to identify optimal hyperparameters. This paper provides an empirical analysis of SVM's hyperparameter tuning by use of metaheuristics. We compare 11 widely known metaheuristics, such as the Genetic Algorithm (GA), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), and Differential Evolution (DE), and employ three common datasets, namely Iris, Breast Cancer Wisconsin, and MNIST, due to their unique characteristics. Empirical analysis takes into account factors including cross-validation, number of agents, noise, and mis-labelled data insertion, with emphasis on performance metrics such as accuracy, number of support vectors, and computational time. Our findings reveal that the PSO outperforms other metaheuristics, followed by the DE and ACO. In addition, we conclude that the ACO has the least computational time.

关键词： Support vector machines Wireless communication Accuracy Reviews Metaheuristics Optimization methods Vectors Particle swarm optimization Tuning Genetic algorithms

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：