检索结果-内蒙古大学图书馆

Consumer Communications and Networking Conference, CCNC IEEE

作者： Maria Mengozzi Manuel Andruccioli Silvia Mirri Giovanni Delnevo Roberto Girau DISI Dept. of Computer Science and Engineering University of Bolgna Bologna Italy

Driving involves numerous factors demanding a driver's attention. To enhance road safety, there has been a significant increase in the development and implementation of vehicle sensors. These sensors, in conjunction with mobile applications, can assess a driver's emotional state and focus, providing feedback to enhance their attention. This paper explores the monitoring of driver behavior, emphasizing the effects of distractions and emotions on driving performance. Stemming from the European initiative, NextPerception, this research focuses on advancing perception sensors and refining distributed intelligence models in various domains, including automotive. The initiative aims to develop a range of sensors, from obstacle detection tools to those monitoring a driver's eye movements and vital signs. A key goal is to define a “fitness-to-drive” metric, representing the driver's attentiveness level. The project also seeks to use gamification to emphasize the importance of this metric, increasing drivers' awareness of their driving skills. The ultimate aim is to create a system that determines fitness-to-drive based on distractions and emotions, integrating this into a prototype simulating sensor data, and introducing a web-based application to display this data for a community of drivers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach to Gun Detection in Surveillance System using YOLOv9

A Deep Learning Approach to Gun Detection in Surveillance Sy...

引用

Control Instrumentation System Conference (CISCON)

作者： Lucy Sumi Shouvik Dey Dept. of Computer Science & Engineering National Institute of Technology Nagaland India

ISBN: (数字)9798350375480

ISBN: (纸本)9798350375497

The escalating firearm related crimes including open firing, robbery, suicides, mass shootings, homicides, threatening at gun point, etc. has underscored the growing importance of timely detection of weapons. This paper presents a gun detection system based on YOLOv9, a state-of-the-art object detection model not previously utilized in literature for gun detection applications. We conduct a comparative analysis with its predecessor versions of YOLOv9, namely YOLOv5, YOLOv6, YOLOv7 and YOLOv8 to assess their performance in gun detection. Our experiments, conducted on a Gun Movie database, reveal that YOLOv9 consistently outperforms its predecessors, demonstrating that YOLOv9 has a good generalizability in detecting firearms in real-time. Particularly noteworthy are the precision and recall values achieved by YOLOv9, reaching 99.6% and 99%, respectively, demonstrating its superior efficacy in accurately identifying guns.

关键词： YOLO Deep learning Firing databases Weapons Surveillance Instruments Motion pictures Control systems Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Eva: Python-based Desktop Virtual Assistant for Visually Impaired

Eva: Python-based Desktop Virtual Assistant for Visually Imp...

引用

International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Anishamol Abraham Benita Susan Mathew Dona Lisa Mathew Fiaz S Mohammad Gokul Krishnan Dept. of Computer Science Amal Jyothi College of Engineering Kottayam India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

Virtual assistants have become essential resources in the digital age, providing users with a wide range of functionalities to expedite work and increase productivity. In this research, we provide a complete examination of Eva, a virtual assistant created using Python, and compare it to other virtual assistants such as Cortana and Copilot. Through a meticulous examination of Eva’s features, we demonstrate its superiority in versatility and effectiveness. By embracing Eva’s strengths and capitalizing on its competitive advantages, we push for a future in which digital experiences are inclusive and empowering for all users.

关键词： Productivity computers Codes Automation Virtual assistants Information age Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

An Intensive Review on Deep Learning Approaches in Non-Invasive Fetal Healthcare Monitoring

An Intensive Review on Deep Learning Approaches in Non-Invas...

引用

Sustainable Expert Systems (ICSES), International Conference on

作者： Harismithaa. LR G. Sudha Sadasivam Dept. of Computer Science of Engineering PSG College of Technology Coimbatore India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Fetal health care is one of the most crucial concerns in today's world. Evaluating fetal well-being has always been challenging. Proper development and monitoring of the fetus are indispensable for its growth and healthy life. Monitoring and diagnosing abnormalities at the right gestational age is very significant. There are remarkable technical advancements in fetal well-being evaluation, bridging the gap between prenatal medicine and Artificial intelligence. This study provides an intensive review of various modes of non-invasive data that can be used for fetal health monitoring and decision support. Also, existing studies on fetal health care that use deep learning techniques for diagnosis and monitoring are explored. Also, a generic framework designed for an Automated Fetal healthcare Monitoring system using AI approaches is presented.

关键词： Deep learning Reviews Medical services Fetus Expert systems Biomedical monitoring Monitoring Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Generation of Correlated Random Numbers with Gaussian Distribution Using Box-Muller's Method and Central Limit Theorem

Generation of Correlated Random Numbers with Gaussian Distri...

引用

International Technical Conference o Circuits/Systems, computers and Communications (ITC-CSCC)

作者： Muhammad Ahmad Abdulfattah Akio Tsuneda Dept. of Computer Science and Electrical Engineering Kumamoto University Kumamoto Japan

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

Generation of high quality Gaussian random numbers is important for simulations across a wide range of disciplines. We investigated the auto-correlation functions of correlated random numbers that follows a Gaussian distribution generated by applying well-known transformation algorithms to uniformly distributed chaotic random numbers generated by 1-dimensional chaotic maps.

关键词： computers Chaotic communication Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

Distinguish Between Obese and Normal Body Types Through Gait Analysis Using Classification Models

Distinguish Between Obese and Normal Body Types Through Gait...

引用

International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Jae-Sik Yi Ji Hun Han Min Jeong Kim Youn-Sik Hong Dept. of Computer Science and Engineering Incheon National University Incheon Korea

For gait analysis, an IMU sensor was mounted on the knee and gait related data was collected. Various gait parameters such as gait time, stance swing ratio, heel strike, and toe off can be extracted from the dataset. To explore the relationship between gait parameters and individual gait characteristics, we analyzed the gait patterns of normal and obese people were analyzed based on BMI (Body Mass Index). To apply it to a classification model of machine learning, different gait cycles between subjects were normalized. Gait data was collected from eight subjects in their 20s. Using this dataset, we applied a logistic regression model, and obtained the classification accuracy of 92%. We also investigated the correlation between BMI and gait parameters and found that, the correlation between BMI and cadence was -0.66.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Gaze into the Pattern: Characterizing Spatial Patterns with Internal Temporal Correlations for Hardware Prefetching

arXiv

引用

arXiv 2024年

作者： Chen, Zixiao Wu, Chentao Gu, Yunfei Jia, Ranhao Li, Jie Guo, Minyi Dept. of Computer Science and Engineering Shanghai Jiao Tong University China

Hardware prefetching is one of the most widely-used techniques for hiding long data access latency. To address the challenges faced by hardware prefetching, architects have proposed to detect and exploit the spatial locality at the granularity of spatial region. When a new region is activated, they try to find similar previously accessed regions for footprint prediction based on system-level environmental features such as the trigger instruction or data address. However, we find that such context-based prediction cannot capture the essential characteristics of access patterns, leading to limited flexibility, practicality and suboptimal prefetching performance. In this paper, inspired by the temporal property of memory accessing, we note that the temporal correlation exhibited within the spatial footprint is a key feature of spatial patterns. To this end, we propose Gaze, a simple and efficient hardware spatial prefetcher that skillfully utilizes footprint-internal temporal correlations to efficiently characterize spatial patterns. Meanwhile, we observe a unique unresolved challenge in utilizing spatial footprints generated by spatial streaming, which exhibit extremely high access density. Therefore, we further enhance Gaze with a dedicated two-stage approach that mitigates the over-prefetching problem commonly encountered in conventional schemes. Our comprehensive and diverse set of experiments show that Gaze can effectively enhance the performance across a wider range of scenarios. Specifically, Gaze improves performance by 5.7% and 5.4% at single-core, 11.4% and 8.8% at eight-core, compared to most recent low-cost solutions PMP and vBerti. Copyright © 2024, The Authors. All rights reserved.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

Automated Grading of Bananas Using Advanced YOLO Models: A Machine Learning and computer Vision Approach for Ripeness Classification

Automated Grading of Bananas Using Advanced YOLO Models: A M...

引用

International Conference on computer and Information Technology (ICCIT)

作者： Md. Sariful Islam Robaaed Afred Tanik Noor Hossain Md Abdur Rahman Tamim Mohammed Imran Jubayer Ahmed Shawon Wahidur Rahman Samia Yasmin Dept. of Computer Science and Engineering Uttara University Uttara Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Among all fruits, bananas are consumed in high quantity around the world, and their health and industrial impact is enormous. The work presented here elaborates on how advanced machine learning and computer vision techniques can automate banana grading, particularly in its different versions of the YOLO model. In that respect, a dataset of 1899 images, representing five stages of ripeness, was manually created and pre-processed. Precision, recall, mean Average Precision at different IoU thresholds, and speed are applied to measure the performances of YOLOv8-n, YOLOv9-s, YOLOv10n, and YOLO11s. The experimental results demonstrated the high value of precision with 0.992 and a recall of 1.0 for the YOLOv8-n model, suitable for real-time applications, whereas YOLO11s attained the highest overall performance in various IoU thresholds with an mAP50-95 of 0.936. This work points out how automated grading systems can play an important role in improving both efficiency and the quality assessment of bananas, promoting consumer satisfaction while reducing post-harvest losses. Further research will be directed toward dataset enlargement, greater application of advanced imaging techniques, and overcoming practical challenges to implementation to improve the accuracy of grading and applicability in real situations, besides establishing a standardized framework for evaluation to gain more widespread acceptance of automated grading technologies in the agricultural sector.

关键词： YOLO computer vision Accuracy Computational modeling Customer satisfaction Imaging Machine learning Real-time systems Quality assessment Information technology

来源：评论

学校读者我要写书评

暂无评论

Survey on Online Learning Applications in Multi-UAV Networks

Survey on Online Learning Applications in Multi-UAV Networks

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Jaemin Kim Hyosu Kim Jeongyeup Paek Yongseok Son Hyung Tae Lee Sungrae Cho Dept. of Computer Science and Engineering Chung-Ang University Seoul Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper provides a comprehensive review of the application of online learning techniques in multi-UAV systems, highlighting their role in enhancing autonomy and efficiency in dynamic environments. Key areas of focus include adaptive path planning, collision avoidance, and swarm behavior control, along with the associated technical challenges and future research directions.

关键词： Surveys Reviews Scalability Reinforcement learning Robustness Real-time systems Path planning Complexity theory Particle swarm optimization Testing

来源：评论

学校读者我要写书评

暂无评论

A Big data Analytic and IoT-Based Approach for Addressing Water Scarcity in Jordan

A Big Data Analytic and IoT-Based Approach for Addressing Wa...

引用

Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Abdelraouf Ishtaiwi Nuha El-Khalili May Alnashashibi Mohammad Abu Arqoub Dept. of Data Science and Artificial Intelligence University of Petra Amman Jordan Department of Software Engineering University of Petra Amman Jordan Department of Computer Science University of Petra Amman Jordan

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Water scarcity critically threatens agricultural sus-tainability in Jordan, necessitating innovative technological solutions. This study presents a comprehensive framework that integrates Internet of Things (IoT) sensors with Big data Analytics to optimize water usage in agriculture. Employing a multi-stage approach, we conducted real-time data acquisition from diverse farms, processed the data using clustering algorithms, and implemented intelligent decision-making systems. Our analysis focused on key parameters such as soil moisture, temperature, rainfall, and wind speed across various farming locations. The methodology encompassed extensive field data collection, advanced analytics, and the deployment of smart irrigation systems. Results demonstrated a significant 25 % reduction in water consumption while maintaining optimal crop yields. Additionally, clustering identified three distinct farm categories, each requiring tailored water management strategies. This research contributes to the field of smart agriculture by providing practical, scalable solutions for regions facing severe water scarcity. The findings highlight the potential of advanced technologies to enhance agricultural sustainability and address critical water management challenges.

关键词： Temperature sensors Smart agriculture Irrigation Wind speed Soil moisture Big data Real-time systems Internet of Things Sustainable development Water resources

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：