检索结果-内蒙古大学图书馆

IEEE 25th international conference on Intelligent Transportation systems (ITSC)

作者： Feng, Zejian Seow, Chee Kiat Cao, Qi Univ Glasgow Sch Comp Sci Glasgow Lanark Scotland

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

Nowadays, the security of Global Navigation Satellite System (GNSS) has raised much more concerns due to the reliance on its position, velocity, and timing (PVT) information, which is of vital importance to various internet of Things (IoT) systems, robotics, 5G technology and many applications of Intelligent Transportation systems (ITSC). It has been shown that GNSS system can be easily spoofed and masqueraded to provide ill intent payload damages. This paper proposes a novel algorithm based on unsupervised machine learning Gaussian Mixture Models (GMM) to provide antispoofing capability of GNSS signal such as GPS signal. It segregates GPS signals that are not under spoofing, from spoofed GPS signals that will result in malicious changes of pseudo-range measurements. It has been found out that the proposed GMM clustering algorithm is able to cluster the positions generated by the un-spoofed GPS signals properly and return the PRN (pseudo-range noise) codes of the satellites without spoofing effectively. The proposed GMM clustering algorithm could cluster the position points generated by nonspoofed signals properly by more than 90% and 77% accuracy for one and three spoofed satellites respectively.

关键词： Global navigation satellite system Machine learning algorithms Satellites Clustering algorithms Machine learning Timing internet of Things

来源：评论

学校读者我要写书评

暂无评论

Design of IoT-based Smart Wearable Device for Human Safety 4th

Design of IoT-Based Smart Wearable Device for Human Safety

引用

4th international conference on IoT based Control Networks and Intelligent systems, ICICNIS 2023

作者： Reddy, Raghavendra Srinivasan, Geethasree Dhaneshwari, K.L. Rashmitha, C. Sai Krishna Reddy, C. School of Computer Science and Engineering REVA University Bangalore560064 India

ISBN: (纸本)9789819965854

Nowadays because of various circumstances, woman and children safety has become very important. There is a need for the smart device which automatically senses and rescues the victims. Proposed new approach helps to use internet of Things (IoT) technology for woman and children safety. The proposed smart wearable device consists of various hardware components and Blynk App. This smart wearable device will communicate continuously with a smart phone through internet service. It makes use of GPS and messaging services to send the location information and alert message. Whenever it receives emergency signal, the system can alert the relevant authorities, nearest police station, relatives, and emergency response teams through automated notifications, allowing them to respond quickly and efficiently. The proposed approach aims to provide a comprehensive solution for women's and child safety and covers the development of application and hardware, including the integration of the alert system and emergency calls and ensuring that the solution is user-friendly, reliable, and effective in critical situations. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Global positioning system

来源：评论

学校读者我要写书评

暂无评论

Deep Learning and Computer Vision based Warning System for Animal Disruption in Farming Environments 3

Deep Learning and Computer Vision Based Warning System for A...

引用

3rd international conference on Artificial Intelligence For internet of Things, AIIoT 2024

作者： Mohanavel, Dhivya Muthu Ishwarya, A. Vellore Institute of Technology School of Advanced Sciences Department of Mathematics Chennai Campus Tamilnadu Chennai600 127 India

ISBN: (纸本)9798350372120

The quarrel between humans and animals due to disruption is cited as a human-wildlife conflict (HWC). These types of incidents frequently leads to a loss of crops, farm animals and humans. In addition to that, it also endangers wildlife species casualty. The local populace in areas where wildlife borders, parks and reserves are close to their dawn have a major dilemma. In this case, animal punishment is not a deterrent. technology-based security patches must be set into practice. The proposed study suggests installation of an animal detection warning system in the form of an alarm set up in the control room to lessen the harm that untamed animals cause to the surroundings and the humans who are employees around. Animal detection can be adapted using deep learning and computer vision (AI) techniques which will be straightforward to locate and identify any creatures that attempt to attack or enter any agricultural field, or farm. The animals are further deterred by alarm systems that provide sound and signals to the field owners and forest officials. In this analysis, with deep learning as a more reliable object identification strategy, YOLO method is used to examine figures incredibly and quickly. Further, the Artificial intelligence (AI field)'s of computer vision enables machines to gather valuable data and to behave appropriately or offer suggestions following the input. These techniques can effectively handle localization, multi-classification, and target that recurs numerously and a danger signal will notify the forest ranger if an animal is spotted or a warning bell will ring at a certain point indicating field owners that animals are close to them. © 2024 IEEE.

关键词： Animals

来源：评论

学校读者我要写书评

暂无评论

Improved Pulse Coupled Neural Network based on Maximize SNR for Vessel Extraction

Improved Pulse Coupled Neural Network based on Maximize SNR ...

引用

2024 international conference on Advancements in Power, Communication and Intelligent systems, APCI 2024

作者： Singh, Davinder Paul Murat Singh, Ram Gopi, T. Deepa, D. Gandhi, K. Parimala Kumar, Divesh Pandit Deen Dayal Energy University Department of Computer Science and Engineering Gandhinagar India Woxsen University School of Technology Telangana India Annamacharya Institute of Technology and Sciences Department of Ece Hyderabad India St Joseph's College of Engineering Department of Ads Chennai India Nehru Institute of Technology Department of Chemistry Coimbatore India Graphic Era Hill University Department of Electronics and Communication Engineering Uttarakhand India

ISBN: (纸本)9798350363289

Aiming at the problems of branch loss and fracture in the fundus retinal vessel segmentation algorithm, with improved pulsed coupled neural network (PCNN) is proposed. As the matched filter can maximize the signal to noise ratio even though using the gaussian filter, therefore, it is used for reducing the noise. First, matching filters are used to enhance the retinal image, and then a segmentation algorithm is suggested using a combination of matching filter and PCNN. Finally, the evaluation on DRIVE database demonstrates that the sensitivity, specificity, and accuracy of the algorithm are 0.7310, 0.9640, and 0.9711 accordingly compared with other algorithms. Simulation experiments illustrate that the Matched-PCNN algorithm resolves the effect of low light and optic disc highlight on vessel segmentation, and demonstrates good connectivity between blood vessels. © 2024 IEEE.

关键词： Matched filters

来源：评论

学校读者我要写书评

暂无评论

Research on surface defect detection of glass wafer based on visual inspection

引用

ENERGY REPORTS 2022年 8卷 381-389页

作者： Huang, Zhangyu Ling, Long Univ Birmingham Dept Elect Elect & Syst Engn Birmingham B152TT W Midlands England Zhuhai Coll Sci & Technol Guangdong Intelligent Vis Precis Detect Engn Tech Zhuhai 519041 Peoples R China

Glass wafer (GW) is used in a variety of integrated circuit (IC) packaging applications and as substrates to provide better performance and cost-effectiveness. Glass wafer (GW) protects the IC from impact and corrosion while maintaining the contract pins and leads that connect it to the external circuit. In the process of technology or production, this kind of structure is continuously working for a long time. Due to the inherent defects such as bubbles generation, starvation and the structure is often suffered from acid, alkali, moisture, vibration and other factors, which makes its internal structure gradually form corrosion stains. These defects have posed a serious threat to the quality and performance of equipment. based on these disadvantages, this paper analyzes the defect detection principle of Glass wafer, then designed a method of determine the defect region. The edge signal processing method of visual image defects is studied, the edge detection and defect feature extraction model is established, and the principle of defining strong and weak edges is clarified. A defect feature classifier based on multi-layer perceptron (MLP) is created, and a segmentation algorithm of the classifier is implemented. Finally, a multi-channel image detection experimental platform is built to verify the typical unit structure. The experimental results show that the rate of defective features recognition is high, the detection rate is fast, and it has practical application value in engineering. The research of this recognition method has positive theoretical significance for accurately evaluating the overall reliability of GW structure and ensuring the safe operation of equipment. (c) 2022 The Author(s). Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the international conference on Energy Storage technology and Power systems, ESPS, 2022.

关键词： Glass wafer (GW) Integrated circuit (IC) Surface defect Defective features recognition Multi-layer perceptron (MLP)

来源：评论

学校读者我要写书评

暂无评论

EMG-based prosthetic arm 1st

EMG-based prosthetic arm

引用

1st international conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Kumar, Nishit Ranjan, Ravi Singh, Sachin Pal, Purnima Department of Electronics & Communication Engineering Noida Institute of Engineering and Technology Noida India

ISBN: (纸本)9781032874036

Advancements in electromyography (EMG) technology have open the wayfor the development of advanced prosthetic arms aimed at providing enhanced functionality and more natural control for individuals with upper limb amputations. This paper provides an overview of an EMG-based prosthetic arm system designed to improve the interaction between users and their prosthetic limbs. The proposed system relies on surface EMG signals produced from muscles in the user’s remaining limb. These signals are captured by a set of electrodes were placed on the skin surface and processed using machine learning algorithms to interpret the user’s intended movements. Through analysis of EMG signal patterns and amplitudes, the system can accurately identify desired actions such as grasping, releasing, and manipulating objects. Incorporating state of art actuation mechanisms and sensory feedback systems, the EMG-based prosthetic arm aims to deliver a more experienced and knowledgeable user. By employing advanced motor control algorithms, the prosthetic armcan replicate human limb movements and exert appropriate forces." Moreover, sensoryfeedback components such as pressure sensors and tactile interfaces allow users to perceive forces and textures during object manipulation, thereby enhancing dexterity and overall functionality. Extensive user trials involving individuals with upper limb amputations have been conducted to evaluate the effectiveness of the EMG-based prosthetic arm system. The results demonstrate notable enhancements in users’ ability to control the prosthetic arm, carry out daily tasks, and experience a sense of embodiment. © 2025 the Author(s).

关键词： Sensory feedback

来源：评论

学校读者我要写书评

暂无评论

6th international conference on Soft Computing and signal Processing, ICSCSP 2023

6th International Conference on Soft Computing and Signal Pr...

引用

6th international conference on Soft Computing and signal Processing, ICSCSP 2023

ISBN: (纸本)9789819986279

The proceedings contain 54 papers. The special focus in this conference is on Soft Computing and signal Processing. The topics include: Stock Price Prediction Using LSTM, CNN and ANN;IoT-based Smart Wearable Devices Using Very Large Scale Integration (VLSI) technology;plant Disease Detection and Classification Using Artificial Intelligence Approach;camera and Voice Control-based Human–Computer Interaction Using Machine Learning;optimal Crop Recommendation by Soil Extraction and Classification Techniques Using Machine Learning;ioT-based Smart Irrigation System in Aquaponics Using Ensemble Machine Learning;Performance Evaluation of MFSK Techniques Under Various Fading Environments in Wireless Communication;prediction of Breast Cancer Using Feature Extraction-based Methods;review and Design of Integrated Dashboard Model for Performance Measurements;anomaly Detection in Classroom Using Convolutional Neural Networks;Efficient VLSI Architectures of Multimode 2D FIR Filter Bank using Distributed Arithmetic Methodology;implementation of an Efficient image Inpainting Algorithm using Optimization Techniques;A Systematic Study and Detailed Performance Assessment of SDN Controllers Across a Wide Range of Network Architectures;Classification and Localization of Objects Using Faster RCNN;an image Processing Approach for Weed Detection Using Deep Convolutional Neural Network;detection of Leaf Black Sigatoka Disease in Enset Using Convolutional Neural Network;detecting Communities Using Network Embedding and Graph Clustering Approach;Deep Learning Approaches-based Brain Tumor Detection Using MRI images—A Comprehensive Review;Predicting Crop Yield with AI—A Comparative Study of DL and ML Approaches;An Empirical Analysis of Lung Cancer Detection and Classification Using CT images;trust and Secured Routing in Mobile Ad Hoc Network Using Block Chain.

关键词：

来源：评论

学校读者我要写书评

暂无评论

6th international conference on Soft Computing and signal Processing, ICSCSP 2023

6th International Conference on Soft Computing and Signal Pr...

引用

6th international conference on Soft Computing and signal Processing, ICSCSP 2023

ISBN: (纸本)9789819984503

关键词：

来源：评论

学校读者我要写书评

暂无评论

Energy performance profiling of a GPU-based CPM implementation

Energy performance profiling of a GPU-based CPM implementati...

引用

international IEEE conference on signal-image Technologies and internet-based System

作者： Pasquale De Luca Ardelio Galletti Livia Marcellino Science and Techonologies Department Parthenope University of Naples Naples Italy

In recent years, there has been a growing interest in the development of in vitro models to predict cellular behavior within living organisms. Mathematical models, based on differential equations and associated numerical algorithms, have been employed for this purpose. In this study, we present initial forays into the design of parallel strategies aimed at accelerating an algorithm for behavior prediction, specifically based on the Cellular Potts Model. To do this, we engage the computational power of Graphic Processing Units within the CUDA environment to optimize critical low-level *** work intends to provide a comprehensive analysis of the energy performance of the proposed implementation. Tests and experiments affirm significant performance gains in terms of both processing time and substantial energy savings.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Traffic Sign Classification based on Deep Learning

Traffic Sign Classification based on Deep Learning

引用

2023 IEEE international conference on Automatic Control and Intelligent systems, I2CACIS 2023

作者： Hongxing, Tian Caballero, Jonathan M. Hernandez, Alexander A. Technological University of the Philippines Graduate Program and External Studies Manila Philippines National University College of Computing and Information Technologies Manila Philippines

ISBN: (纸本)9798350321302

In the context of 5G communication, technologies such as the internet of Things, big data, and supercomputers have been further developed, and artificial intelligence technology has also become one of the hot topics at present. In recent years, the image recognition technology of artificial intelligence has been pursued by most academic enthusiasts and has been rapidly developed. With the development of computer vision, a series of target detection algorithms have emerged in recent years. This paper classifies traffic signs based on the target detection algorithm of YOLOv5 and make use of the advantages of the accuracy and real-time performance of the YOLO algorithm. To restore the real traffic scene, different shooting angles and different shooting locations are prepared as data sets. Finally, to realize the detection and recognition of traffic signs and optimize the algorithm to improve the recognition rate. © 2023 IEEE.

关键词： Traffic signs

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：