2022 IEEE Bombay Section Signature Conference (IBSSC)最新文献_第4页

TransUnet for psoriasis lesion segmentation TransUnet用于银屑病病灶分割

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037394

Samiksha Soni, N. Londhe, RITESH RAJ, Rajendra S. Sonawane

引用次数: 1

Simulation And Real Time Of VR Controlled Robotic Manipulator Using ROS 基于ROS的VR控制机械臂仿真与实时性研究

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037520

Sasidharan Vairavasamy, Noel Innocent J, Hamin Mj, S. Ahmed, Seenu N, Ramya MM Dean

引用次数: 0

Fraud Detection and Monitoring of Water Tankers using IoT 使用物联网的水车欺诈检测和监控

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037515

D. Pawade, Avani M. Sakhapara, Irfan A. Siddavatam, Mishtee Gandhi, Akshata Ingalahalli, A. Dalvi

{"title":"Fraud Detection and Monitoring of Water Tankers using IoT","authors":"D. Pawade, Avani M. Sakhapara, Irfan A. Siddavatam, Mishtee Gandhi, Akshata Ingalahalli, A. Dalvi","doi":"10.1109/IBSSC56953.2022.10037515","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037515","url":null,"abstract":"During the water crisis, water supply through tanker is a common scenario in India. Most of the time, Government hires private tankers on contract basis to distribute the water and pays them based on the number of trips. It is observed that the tanker contractors show fake trips and fraudulently charge for it. To avoid so, roster is maintained which has entry for each trip. Yet this is not sufficient to control the malpractices. It might be possible that, from the source, the entry for the tanker trip is made in roster but there is no guarantee that tanker will reach to the specified destination. In between the tanker driver can sell that water to someone else. Sometimes the tanker reaches to the desired destination but in between half of the water is sold. Thus, the intended beneficiaries don't get enough water. Many times, muddy and contaminated water is being distributed which may lead to many health issues. Thus, there is a need of some automated mechanism using which Government officials can keep track of tanker movement, check the quantity and quality of the water. This motivated us to come up with IoT based solution which comprise of various sensors to collect the data such as GPS location of tanker, level of water, pH and turbidity value of water. This data is stored over a cloud and made available through a web application. This way the Government officials can get consolidated report as well as alerts if any malpractice is carried out.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131432827","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

Performance Analysis of Machine Learning Algorithms for COVID-19 Detection 新型冠状病毒检测机器学习算法性能分析

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037516

A. Thakare, Pranjali G. Gulhane, S. Chaudhari, H. Baradkar

{"title":"Performance Analysis of Machine Learning Algorithms for COVID-19 Detection","authors":"A. Thakare, Pranjali G. Gulhane, S. Chaudhari, H. Baradkar","doi":"10.1109/IBSSC56953.2022.10037516","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037516","url":null,"abstract":"The Novel Coronavirus Illness 2019 (COVID-19) was found in Wuhan, Hubei, China, in December 2019 and has since spread globally. When the patient's corona sickness worsened, his life was in danger. Coronavirus assaults the lungs. Diagnostic kits today only search for viral illnesses, which deceives doctors. All patients receiving the same treatment harm patients with less infection. This publication describes non-invasive treatment for infected people. Dissecting chest X-ray pictures to examine the coronavirus helps investigate and predict COVID-19 patients. We offer a hybrid method for detecting Covid. CNN and SVM identify Covid. Because X-ray pictures are inconsistent, CNN is used for feature extraction. To construct a training dataset before CNN, we used data augmentation. Data augmentation increases the training dataset's amount and quality. SVM is used for classification since it tolerates feature differences. The main goal is to help clinical doctors determine the severity of a chest infection so they can administer life-saving treatment. Deep learning and machine learning-based techniques will determine the degree of chest infection and lead to optimal medication, avoiding expensive treatment for all patients.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125519517","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

Major and Sub-Class Classification of Arrhythmia using Eigen Vectors in ConvNet 基于卷积神经网络特征向量的心律失常主次类分类

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037262

S. Umamaheswari, D. Sangeetha, S. Sriram, J. Nandhinipriva

{"title":"Major and Sub-Class Classification of Arrhythmia using Eigen Vectors in ConvNet","authors":"S. Umamaheswari, D. Sangeetha, S. Sriram, J. Nandhinipriva","doi":"10.1109/IBSSC56953.2022.10037262","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037262","url":null,"abstract":"Cardiac Arrhythmia is a heart disease that corresponds to abnormal rhythm of heart. It means that the heart is either beating too quickly, too slowly, or sporadically. Arrhythmia is recognized and categorized effectively so as to improve the living conditions of the patients. The Electro Cardiogram (ECG) is a tool for recording electrical activity and determining the electrical impulses in the heart. There are four main classes of arrhythmia which occur due to abnormal heartbeat which are being classified. The main objective of this proposed work is to provide better performance in predicting arrhythmia since even a small error can become dangerous to a person's life. The existing methods uses CNN as the feature extraction model which delays the time of prediction. Here, a novel feature extraction method is introduced based on 1D-Convolutional Neural Networks using the Eigen Vectors functionality. This feature extraction model proves to outperform the existing works in accurately classifying the different classes of arrhythmia. Finally, the ANN model is trained using the K-fold Cross Validation method to achieve this performance and is compared with an ensemble model containing a SVM, ANN and a Decision Tree.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128345875","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

A Comparative Study on Data Mining Classifiers to Predict Lung Cancer and Types of NSCLC 数据挖掘分类器预测肺癌和非小细胞肺癌类型的比较研究

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037478

R. Adsul, Vedant Misra, Saumya Pailwan

引用次数: 0

ROI based real time straight lane line detection using Canny Edge Detector and masked bitwise operator 基于Canny边缘检测器和掩码位算子的实时直线检测

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037363

Manan Doshi, Harsh Shah, Neha Katre

{"title":"ROI based real time straight lane line detection using Canny Edge Detector and masked bitwise operator","authors":"Manan Doshi, Harsh Shah, Neha Katre","doi":"10.1109/IBSSC56953.2022.10037363","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037363","url":null,"abstract":"Research for autonomous cars has now been close to a decade and still it is not possible to employ these cars everywhere around the world, for one major reason being clear lane line detection. However, there is constant discovery to improve the method of lane detection, especially in real-time. For lane detection, various computer-vision techniques and deep learning models have been devised, but for practical use it is necessary to find an efficient solution in real-time. Our technique is based on the real-time efficient detection of straight lanes using a canny edge detector followed by finding a region of interest and Hough transformation. This method takes video as an input and gives outputs in the form of images with slopes and marked lines of lanes. For long highways with straight lanes, this algorithm can prove to be extremely efficient for detection, which can be easily employed in real-time using camera sensors that provide a video feed. Furthermore, there is no requirement for training the algorithm. Hence, this system works on most of the scenarios without any prior data training.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133809953","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

Explainable Approach for Species Identification using LIME 利用石灰进行物种鉴定的可解释方法

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037417

Mihir Nikam, Ameya Ranade, R. Patel, Prachi Dalvi, Aarti M. Karande

{"title":"Explainable Approach for Species Identification using LIME","authors":"Mihir Nikam, Ameya Ranade, R. Patel, Prachi Dalvi, Aarti M. Karande","doi":"10.1109/IBSSC56953.2022.10037417","DOIUrl":"https://doi.org/10.1109/IBSSC56953.2022.10037417","url":null,"abstract":"Plant identification has a wide array of applications in the fields of agronomy and the discovery of natural and medicinal products. This research aims to explore various deep learning techniques like InceptionV3, Xpection, and ResNet to identify plants. Highly accurate machine learning models generally lack explainability and interpretability. Neural networks are usually opaque systems and thus a direct understanding of the interpretations becomes necessary. We aim to remove this ambiguity of how the model reaches its conclusion by introducing Explainable AI (XAI) techniques. Explainability aims to break such barriers by diminishing the lack of transparency in Artificial Intelligence and Machine Learning models, thus taking a step toward making AI reliable. In this paper, Convolutional Neural Network has been used to identify Vietnamese medicinal plant images based on the characteristics of the leaves, stems and other parts of the plant. Upon identification, our paper also elaborates on how each model predicts which part of the image helps the CNN model to make a prediction by integrating Explainable AI (XAI) using the Lime package. Through this research, we generated images using LIME package which highlight pixels that determine the result of our plant identification process.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"63 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125944090","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

Diabetes Detection Using Machine Learning Algorithms 使用机器学习算法检测糖尿病

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037329

Nicole D'Souza, K. Shah, Pranav Singh

引用次数: 0

Wireless Charging in a Dynamic Environment for Electric Vehicles 电动汽车动态环境下的无线充电

2022 IEEE Bombay Section Signature Conference (IBSSC) Pub Date : 2022-12-08 DOI: 10.1109/IBSSC56953.2022.10037388

Sandeep Ushkewar, Gaurav B. Patil, Vishal Moyal

引用次数: 1