2023 IEEE 8th International Conference for Convergence in Technology (I2CT)最新文献_第10页

A Novel approach to Handle Imbalanced Dataset in Machine Learning 机器学习中一种处理不平衡数据集的新方法

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126309

Taj Sapra, Shubhama, S. Meena

引用次数: 0

Performance Analysis of Machine Learning Algorithms to Predict Cardiovascular Disease 预测心血管疾病的机器学习算法性能分析

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126428

Hridya V Ramesh, Rahul Krishnan Pathinarupothi

{"title":"Performance Analysis of Machine Learning Algorithms to Predict Cardiovascular Disease","authors":"Hridya V Ramesh, Rahul Krishnan Pathinarupothi","doi":"10.1109/I2CT57861.2023.10126428","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126428","url":null,"abstract":"Globally the rate of heart disease has increased drastically due to unhealthy eating habits and reduced physical activities. It has become one of the significant causes of death worldwide. As per the reports of the world health organization(WHO), 31% of all deaths worldwide are caused by cardiovascular diseases. This demands the development of a system capable of early detection of cardiovascular diseases at an affordable cost. With this as the objective, multiple machine learning algorithms have been selected to evaluate their performance in the early detection of cardiovascular diseases. This work utilizes available data sets of an individual’s vital parameters, demographic data, and exercise parameters for predicting cardiovascular diseases. An extensive evaluation is performed to identify the best-suited supervised machine learning classifier that could predict cardiovascular diseases using the available datasets. This research work details the nine different classification algorithms utilized for this analysis. For each algorithm, the F1-score, precision, recall, accuracy, and Area Under the Receiver Operating Characteristics (AUROC) values for each model have been determined and compared with the rest of the algorithms. The results show that random forest and gradient boosting models outperform others and demonstrate an F1-Score of 0.88 and an AUROC value of 0.92, respectively. This showcases that doctors could utilize this technique for the early identification of cardiovascular diseases. This will provide the opportunity to offer adequate medical treatments early, thus saving lives.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116332368","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 Fractional-Order Microwave Bandpass Filter for 5G Applications 面向5G应用的分数阶微波带通滤波器性能分析

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126373

Priyanka Priyadarsinee, Sumit Swain, Satyabhama Dash, M. Tripathy

引用次数: 1

License Plate Recognition for Detecting Stolen Vehicle Using Deep Learning 利用深度学习检测被盗车辆的车牌识别

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126393

Atul B. Kathole, Ajim Shikalgar, Nitish Supe, Tejasha Patil

{"title":"License Plate Recognition for Detecting Stolen Vehicle Using Deep Learning","authors":"Atul B. Kathole, Ajim Shikalgar, Nitish Supe, Tejasha Patil","doi":"10.1109/I2CT57861.2023.10126393","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126393","url":null,"abstract":"India is anticipated to overtake China as the third-largest vehicle market in the near future. Vehicle theft, according to data, has increased yearly. But the proportion of cases that the police really resolve is still quite small. It is challenging for police to locate stolen vehicles since they are sometimes carried to locations distant from the scene of the theft. Therefore, a need for an automated system to assist in tracking such cars arises. These issues are what our project tries to fix. The police will receive a tonne of information from this system that they may utilise to solve theft cases. Using the YOLO V3 algorithm and Canny Edge Detection, the identification system will automatically recognize automobile license plate numbers. After a license plate is identified, the following actions are taken: 1. to photograph the license plate. 2. to recognize and divide characters. 3. The time and date are then recorded in a database together with the identifying license plate for further use. 4. In the event that a stolen vehicle is discovered, a thorough report detailing the location and the time the vehicle first appeared is prepared, and police are notified that a match has been made. The method may be applied to increase security and accuracy.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125123463","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

Recognition of Tomato Leaf Disease Using 10-Layered DCNN 基于10层DCNN的番茄叶病识别

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126179

N. VinaySeshu, A.G.K. SriHarsha, D. Shivareddy, K. Swaraja, N. Sreekanth, C. Sujatha

引用次数: 0

A Comprehensive Review of Image Colorization Methods 图像着色方法综述

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126250

A. Deo, S. Shinde, Tejas Borde, Suraj Dhamak, Shreyas Dungarwal

引用次数: 0

Comparative Study with Fuzzy Logic System for Renewable Green Energy Generation 与模糊逻辑系统在可再生绿色能源发电中的比较研究

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126225

Dipali Padwad, H. Naidu

{"title":"Comparative Study with Fuzzy Logic System for Renewable Green Energy Generation","authors":"Dipali Padwad, H. Naidu","doi":"10.1109/I2CT57861.2023.10126225","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126225","url":null,"abstract":"Renewable green energy generation with the study of biomass growth potential of plants using artificial light without any damage to environment is being experimented and the fuzzy logic is being implemented to compare with the actual experimental results. Plants are available abundantly in nature across the globe and become more useful by knowing the electric generation potential inside it which acts as an alternative energy source to curtail the CO2 emission as well as environmental temperature to prevent global warming. In this paper, Plant Microbial Fuel Technology (PMFC) is used on Marigold, Rose plant, Nerium Oleander, Coriander, Mustard, Tomato and Mint plants for generation of green electricity using copper and iron electrodes including study of biomass growth potential. The results are satisfactory since it concludes that hidden potential of generation of electricity and the biomass growth potential enhanced due to wavelength variations of artificial light. The voltage obtained in the plants is enhanced by introducing Boost converter model which is simulated in the MATLAB software and gave satisfactory results.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126864911","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

Smart Traffic Light Switching and Traffic Density Calculation Model using Computer Vision 基于计算机视觉的智能交通灯切换与交通密度计算模型

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126240

Sarvesh Ransubhe, Mohammad Abdul Mughni, Chinmay R. Shiralkar, Bhakti Ratnaparkhi

引用次数: 1

Convolutional Networks for Skeleton-Based Gesture Recognition Using Spatial Temporal Graphs 基于骨架的基于时空图的手势识别卷积网络

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126371

Soumya Jituri, Sankalp Balannavar, Shri Nagahari Savanur, Guruprasad Ghaligi, A. Shanbhag, Uday Kulkarni

{"title":"Convolutional Networks for Skeleton-Based Gesture Recognition Using Spatial Temporal Graphs","authors":"Soumya Jituri, Sankalp Balannavar, Shri Nagahari Savanur, Guruprasad Ghaligi, A. Shanbhag, Uday Kulkarni","doi":"10.1109/I2CT57861.2023.10126371","DOIUrl":"https://doi.org/10.1109/I2CT57861.2023.10126371","url":null,"abstract":"In the recent years, recognition of human actions and the interactions of human body bones provide crucial data. It has been applied in many fields from video intelligence to computer vision. The idea behind working of these have a common approach of using deep learning methods that include Convolutional Networks. The Graph convolution networks (GCN) is extensively used in recognition of skeleton action-based data. We point out that current GCN-based methods generally rely on specified graphical patterns (i.e., a hand-crafted structure of the joints in the skeleton), which hinders their potential to gather intricate connections between joints. Thus a better advanced model can be proposed out of the GCN-based model. This paper aims in delivering a novel model of Spatial Temporal Graph Convolutional Networks (ST-GCN) are interactive skeletons that learn from the spatial and temporal variability of input data(ST-GCN) [1]. We here use a large dataset –Kinetics to perform the analysis and predict the output for given skeletal data.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127827519","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

Smart Traffic Signal Management System 智能交通信号管理系统

2023 IEEE 8th International Conference for Convergence in Technology (I2CT) Pub Date : 2023-04-07 DOI: 10.1109/I2CT57861.2023.10126180

Rachuri Sai Manasa, Jatoth Madhu, MD Sufiyanuddin, Patil Mounica

引用次数: 0