2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)最新文献_第9页

Iot Based Smart Irrigation and Monitoring System 基于物联网的智能灌溉与监控系统

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074469

Aman Sharma, Abhinav Singh Patel, Avinash Kaushal

引用次数: 0

ConvXGDFU - Ensemble Learning Techniques for Diabetic Foot Ulcer Detection 用于糖尿病足溃疡检测的集成学习技术

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/icac3n56670.2022.10074466

Priyansh Kedia, Priyansh Soni, Pranjal Gupta, Rohan Pillai, A. Chaudhary

{"title":"ConvXGDFU - Ensemble Learning Techniques for Diabetic Foot Ulcer Detection","authors":"Priyansh Kedia, Priyansh Soni, Pranjal Gupta, Rohan Pillai, A. Chaudhary","doi":"10.1109/icac3n56670.2022.10074466","DOIUrl":"https://doi.org/10.1109/icac3n56670.2022.10074466","url":null,"abstract":"Medical practitioners have been studying Diabetic Foot Ulcers (DFU) as a critical subject for treatment purposes. The fundamental objective is to achieve a mechanism for early detection and identification of DFU, ensuring effective treatment before progressing to a critical stage. The traditional clinical techniques have drawbacks, such as a high diagnosis cost, high clinical workload, and an extended treatment time. Moreover, the cost of delayed detection and treatment can lead to significant significance. Although this approach yields outstanding results, a remote, cost-effective, and easy DFU diagnostic method is required. In recent times, Machine Eearning and Deep Learning methods have proven to be very effective and efficient in medical diagnosis and disease detection. The fundamental objective of this study is to build an efficient Artificial Intelligence model for detecting DFUs. We have proposed a novel Deep Learning model using CNNs and XGBoost for DFU detection. Our proposed model is called ConvXGDFU, which can efficiently classify DFU vs Normal Skin patches. Results show that our devised model achieved an accuracy and F1 score of 99.90% and 99.60% for both classes.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121121862","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

Sentimental Analysis Using Deep Learning Techniques 使用深度学习技术进行情感分析

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074475

S. Kumari, Jayakumar V

引用次数: 10

A Study of LSTM in Stock Price Prediction LSTM在股票价格预测中的研究

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074373

Ishan Adhikari Bairagi, A. Daniel, Anchal Sharma

{"title":"A Study of LSTM in Stock Price Prediction","authors":"Ishan Adhikari Bairagi, A. Daniel, Anchal Sharma","doi":"10.1109/ICAC3N56670.2022.10074373","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074373","url":null,"abstract":"Investing into stocks has become a trend in the new generation and everyone shows keen interest in putting their money and trying their luck into the stock game. But it requires deep analysis and thorough knowledge to get you through the risk and failures. There are multiple platforms which let you invest money into stocks nationally and internationally and with the boom in cryptocurrency, it has become evident that investments are an efficient way to earn and give us an upper hand over others as far as income parameters are concerned. This project aims to predict the price of the selected stock and give useful and near reliable insights so that investor can have an idea of how the stock may perform in the future. This can really help assess the performance of a stock and make calculated decisions. We intend to predict the stock using the LSTM neural network and then at a later stage provide the user with a dashboard using plotly dash for stock analysis. However stock prices are subject to market conditions and may change abruptly depending on multiple factors. Thus the project aims to give supposed prices to the investor on an approximate basis. The future of this project can be made in a mobile based app which plugged in with previous performance of stock data will help users take advantage of the prediction at their hands.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121725672","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

COVID 19 Prediction Using Chest X-Ray And CNN Hyperparameter Optimizer 基于胸部x射线和CNN超参数优化器的COVID - 19预测

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074127

Satwik Ghosh, Koustav Ghosh, Ayan Mondal, Mainak Ghosh, Tapan Chowdhury

引用次数: 0

House Price Prediction using regression techniques 运用回归技术预测房价

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074128

Rupam Dwivedi, R. Gupta, Prashant Kumar Pal

{"title":"House Price Prediction using regression techniques","authors":"Rupam Dwivedi, R. Gupta, Prashant Kumar Pal","doi":"10.1109/ICAC3N56670.2022.10074128","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074128","url":null,"abstract":"Real estate companies keep special care when they purchase or sell a new house. A significant amount of expertise and market awareness is required for making accurate price predictions of houses so as to turn it out into a profitable investment. Also, the setting of prices manually is quite difficult and tedious task and the accuracy of prediction done by the real estate experts is also not good in that case due to the probability of human errors. The primary goal of this project is to provide the best and most profitable house price predictions to real estate investors with the help of a machine learning model so that they can get best returns in their deals as per the market scenario. It can also provide a lot of convenience to buyers who want to purchase a house at best market prices depending upon the desired house features. It consists of a ML-based model which mainly involves the use of three machine learning algorithms namely linear regression, decision tree regression and random forest regression. Three individual models are created on the basis of each of these algorithms and the most suitable model with maximum accuracy is chosen. With the analysis of various features and specifications of the houses such as number of rooms, locality, population status, physical conditions etc., prices will be estimated.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122905555","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: 1

Learning Management System: An Approach towards Virtual Education 学习管理系统:迈向虚拟教育的途径

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074184

Avneesh Pathak, J. Singh, A. Singhal, Vishwadeepak Singh Baghela

引用次数: 0

Automatic Detection of Rice Diseases using Deep Convolutional Neural Networks with SGD and ADAM 基于SGD和ADAM的深度卷积神经网络水稻病害自动检测

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074538

Pardeep Seelwal, Alok Sharma

{"title":"Automatic Detection of Rice Diseases using Deep Convolutional Neural Networks with SGD and ADAM","authors":"Pardeep Seelwal, Alok Sharma","doi":"10.1109/ICAC3N56670.2022.10074538","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074538","url":null,"abstract":"Rice diseases are the major problem in all over the world of agriculture sector. The early detection of this disease will prevent the huge economic loss for the farmer. This paper proposes a deep learning algorithm to classify the disease in the rice plant. Images of healthy and blast disease affected leaves are taken for the proposed system. The features are extracted for the healthy and brown spot, leaf blast, hispa disease of the rice leaf. The total data set is divided for training and testing purposes. These images are processed with the proposed multi-classification method and the leaf is categorized into brown spot, leaf blast, hispa disease and healthy. In this work CNN model is employed using two different optimizers i.e. SGD and ADAM. It is found that SGD performed well as compared to ADAM for our application as the training accuracy is obtained from proposed model with ADAM optimizer is 92.04 % while with SGD produced the training accuracy 96.32 %.The proposed model capable of getting promising accuracy for healthy and brown spot, leaf blast, hispa disease of the rice using multi-classification model.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133155312","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: 1

Smart Voice Assitance System for Visually Impaired Persons 视障人士智能语音辅助系统

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074529

P. Manikandan, G. Ramesh, P. Syam Mohan Reddy, J. Suman, M. Dhanush Vasavai Kumar, K. R. Chandra Siddhardha Reddy

引用次数: 2

IoT Based Smart Home Automation Using Solar Panel System 使用太阳能电池板系统的基于物联网的智能家居自动化

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074456

Ayan Ahmad Khan, D. Kumar, T. Bahar

引用次数: 0