2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)最新文献_第3页

UAV Aerial Survey and Communication 无人机航测与通信

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663727

S. Samanth, K. Prema, Mamatha Balachandra

{"title":"UAV Aerial Survey and Communication","authors":"S. Samanth, K. Prema, Mamatha Balachandra","doi":"10.1109/DISCOVER52564.2021.9663727","DOIUrl":"https://doi.org/10.1109/DISCOVER52564.2021.9663727","url":null,"abstract":"Over the past several decades, Unmanned Aerial Vehicles (UAVs) have been used in a variety of applications with 2 basic classifications of UAVs’ a scivilian and military drones. Drones capture a variety of multimedia data. Among the multimedia data, images with overlapping regions need to be stitched to generate a panorama which would provide image data of ‘n’ number of images captured by a drone. The data captured by drones should be effectively communicated to a Ground Control Station (GCS). Hence in the research, 4 drones capture both text data and images. Each drone generates a corresponding panorama for the set of images captured by it and communicates both its text data and panorama to the GCS. 2 desktops are used for performing the experiments using client-server communication. Client desktop is used for performing simulations using AirSim simulator (which consists of 4 drones) on the Unreal Engine 4.25 platform, and generate panoramas for the set of images captured by each drone. Server desktop acting as GCS is used to accumulate text data and image data from 4 drones. Image stitching analysis has been done using 2 Python versions and Open CV versions, and 2 AirSim environments. Image stitching results were more effective with the use of Python version 3.7.1 and Open CV version 3.4.2 pair (image stitching success rate, and image stitching accuracy = 100%) when compared to that with Python version 3.9.1 and Open CV version 4.5.2 pair (image stitching success rate = 75%, image stitching accuracy = 33.33%). Both the text data and panoramas from 4 drones were successfully transmitted to the GCS.","PeriodicalId":413789,"journal":{"name":"2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132318819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Grammatical Tagging for the Kannada Text Documents using Hybrid Bidirectional Long-Short Term Memory Model 基于混合双向长短期记忆模型的卡纳达语文本语法标注

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663430

A. Ananth, Sachin S. Bhat, P. S. Venugopala

引用次数: 1

Chronic Kidney Disease Detection from Clinical Data using CNN 使用CNN从临床数据中检测慢性肾脏疾病

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663670

D. Pavithra, R. Vanithamani

引用次数: 1

Real Time Patient Monitoring System Using BLYNK 使用BLYNK的实时病人监护系统

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663681

S. Ranjana, Ramakrishna Hegde, C. Divya

引用次数: 3

A Proposed Model on Merging IoT Applications and Portable EEGs for Migraine Detection and Prevention 一种融合物联网应用和便携式脑电图的偏头痛检测和预防模型

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663615

Akhila Jagarlapudi, Amey Patil, D. Rathod

引用次数: 1

Recognition of Moving Vehicle Number Plates using Convolutional Neural Network and Support Vector Machine Techniques 基于卷积神经网络和支持向量机技术的移动车牌识别

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663618

Roshan Fernandes, K. Madhu Rai, Anisha P. Rodrigues, B. A. Mohan, N. Sreenivasa, N. Megha

{"title":"Recognition of Moving Vehicle Number Plates using Convolutional Neural Network and Support Vector Machine Techniques","authors":"Roshan Fernandes, K. Madhu Rai, Anisha P. Rodrigues, B. A. Mohan, N. Sreenivasa, N. Megha","doi":"10.1109/DISCOVER52564.2021.9663618","DOIUrl":"https://doi.org/10.1109/DISCOVER52564.2021.9663618","url":null,"abstract":"Nowadays video cameras have become gradually deployed, hence the hassle of video enhancement has also been increased. Video enhancement is a process of illuminating the occurrence using gentle techniques to maintain the integrity of pixel quality. The standard of the original video recording gives the success for the enhancement. The purpose of video enhancement is to refine the visual look of the video or to give an extra changed illustration for future video processing which consists of analysis, detection, segmentation, recognition, and used for surveillance and the criminal justice system. In the proposed work vehicle number plate is enhanced and recognition of a number plate is performed using Convolutional Neural Network and Support Vector Machine. There are a lot of challenges in recognizing the number plate due to the presence of blur, low-intensity, snow, rain, hit and run cases. In such a case, recognizing the vehicle number plate is challenging. So to overcome all these problems video enhancement has to be performed. The proposed work involves converting the video into image frames, pre-processing the frames and then performing enhancement, and finally recognizing the vehicle number plate using CNN and Support Vector Machine. The result analysis proves that CNN gives better classification accuracy over the Support Vector Machine model.","PeriodicalId":413789,"journal":{"name":"2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121731834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Design and Development of an Instrumentation System to Detect the Bioelectric Signals of Plants 植物生物电信号检测仪器系统的设计与开发

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663601

K. Kailash Chandra Shenoy, Sukesh. Rao

引用次数: 1

Hierarchical Modeling of Binding Affinity Prediction Using Machine LearningTechniques 基于机器学习技术的绑定亲和预测分层建模

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663690

Sofia D'souza, K. Prema, S. Balaji

引用次数: 1

SLA Violation Detection in Multi-Cloud Environment using Hyperledger Fabric Blockchain 基于Hyperledger Fabric区块链的多云环境下SLA违规检测

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663620

P. Abhishek, Akash Chobari, D. Narayan

{"title":"SLA Violation Detection in Multi-Cloud Environment using Hyperledger Fabric Blockchain","authors":"P. Abhishek, Akash Chobari, D. Narayan","doi":"10.1109/DISCOVER52564.2021.9663620","DOIUrl":"https://doi.org/10.1109/DISCOVER52564.2021.9663620","url":null,"abstract":"The increased usage of cloud computing technology and its industry-wide adoption has led to almost all modern consumer services being heavily dependent on cloud computing platforms. The user and the Cloud Service Provider (CSP) must agree on a Service Level Agreement (SLA) to keep performance above a given threshold and maintain a certain Quality of Service (QoS) (quality of service). This SLA is enforced by the CSP, who monitors the performance of the computers and compensates the user using the logs created by the underlying machinery. Similarly, a cautious customer can keep a monitoring system in place to examine the operation of the virtualized resources assigned to them regularly. This leads to distrust between the CSP and the customer, as neither party believes the other’s monitoring system is reliable. In this work, we propose a blockchain-based which guarantees the integrity of the client’s logs and verifies the SLA violations creating a trustworthy ecosystem. Furthermore, we carry out the scalability and performance analysis of proposed system using Hyperledger Fabric blockchain platform.","PeriodicalId":413789,"journal":{"name":"2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132931447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Microstrip Antenna Using Metamaterials For Satellite Communication 卫星通信用超材料微带天线

2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) Pub Date : 2021-11-19 DOI: 10.1109/DISCOVER52564.2021.9663688

F. V. Jayasudha, I. Sheeba, I. S. Sanju, K. Srilatha

引用次数: 0