2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)最新文献_第4页

NDVI based Image Processing for Forest change Detection in Sathyamangalam Reserve Forest 基于NDVI的Sathyamangalam保护区森林变化检测

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988184

Giridharan N, S. R

引用次数: 0

Deep Learning Based Facemask Detection 基于深度学习的面罩检测

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9987782

Priscilla Whitin, V. Jayasankar

引用次数: 0

Analysis of Various Regressions for Stock Data Prediction 股票数据预测的各种回归分析

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9987844

M. Reddy, R. Sumathi, N. K. Reddy, N. Revanth, S. Bhavani

引用次数: 0

A Revised Converter Paradigm Designed for Spam Message Exposure 针对垃圾邮件暴露设计的改版转换器范例

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988465

K. S, T. Vyshnavi, Yaragandla Mounika, S. Tejaswini

引用次数: 0

A Proficient and secure way of Transmission using Cryptography and Steganography 使用密码学和隐写术的一种熟练和安全的传输方式

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988094

G. D. Reddy, Yaddanapudi Vssrr Uday Kiran, Prabhdeep Singh, Shubhranshu Singh, Sanchita Shaw, Jitendra Singh

{"title":"A Proficient and secure way of Transmission using Cryptography and Steganography","authors":"G. D. Reddy, Yaddanapudi Vssrr Uday Kiran, Prabhdeep Singh, Shubhranshu Singh, Sanchita Shaw, Jitendra Singh","doi":"10.1109/ICTACS56270.2022.9988094","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988094","url":null,"abstract":"People are concerned about the security of their data over the internet. The data can be protected in many ways to keep unauthorized individuals from accessing it. To secure data, steganography can be used in conjunction with cryptography. It is common for steganography to be used for hiding data or secret messages, whereas cryptography encrypts the messages so that they cannot be read. As a result, the proposed system combines both cryptography and steganography. A steganographic message can be concealed from prying eyes by using an image as a carrier of data. In steganography, writing is done secretly or covertly. The digital steganography algorithm uses text, graphics, and audio as cover media. Due to recent advancements in technology, steganography is challenging to employ to safeguard private data, messages, or digital photographs. This paper presents a new steganography strategy for confidential communications between private parties. A transformation of the ciphertext into an image system is also performed during this process. To implement XOR and ECC (Elliptic Curve Cryptography) encryption, three secure mechanisms were constructed using the least significant bit (LSB). In order to ensure a secure data transmission over web applications, both steganography and cryptography must be used in conjunction. Combined techniques can be used and replace the current security techniques, since there has been an incredible growth in security and awareness among individuals, groups, agencies, and government institutions.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134620139","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

Machine Learning for Auto Segregation of Fruits Classification Based Logistic Support Vector Regression 基于Logistic支持向量回归的水果分类自动分离机器学习

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988523

V. Ghodke, S. S. Pungaiah, M. Shamout, A. A. Sundarraj, Moidul Islam Judder, S. Vijayprasath

{"title":"Machine Learning for Auto Segregation of Fruits Classification Based Logistic Support Vector Regression","authors":"V. Ghodke, S. S. Pungaiah, M. Shamout, A. A. Sundarraj, Moidul Islam Judder, S. Vijayprasath","doi":"10.1109/ICTACS56270.2022.9988523","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988523","url":null,"abstract":"In agriculture, automation is an important attribute for improving and enhancing the quality, expansion and efficiency of the products produced. The quality of the rating has been reduced as the product classification has improved. Sorting is one of the most important challenges in the industry, so need a reliable segregation system that allows us to package our products easily and automatically. Features used in this process include pre-processing, entry, division, extraction, classification, and detection. Existing approaches is not accurately finding the fruit result and take more time take to finding the segregation part. To overcome the issue in this work proposed the method Logistic Support Vector Regression (LSVR) is efficient classified the fruits images. Initially start the process include the image dataset, and first step is preprocessing. In this stage, remove unwanted areas of images, to check the imbalanced values and eliminating the image defects. Next step segmenting the images form the stage of preproceeing filtered images, it helps to splitting the images. Extracting the features based on the images weightages and evaluating for classification. Then using the training and testing images for classification, it includes segregating or identifying color, texture, shape, and defects. Finally, classification using LSVR process improves images quality and assists the industry in segregating products. The use of images in the automated packaging process improves the quality of the results in a better way than ever before. Use this approach and smart logistics to keep track of the transaction process. The purpose of this work is primarily to minimize or eliminate waste.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130392101","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

Voting Classification Approach for Covid-19 Prediction with K-mean and PCA 基于k均值和PCA的Covid-19预测投票分类方法

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988385

Neha Sharma, Deeksha Kumari

{"title":"Voting Classification Approach for Covid-19 Prediction with K-mean and PCA","authors":"Neha Sharma, Deeksha Kumari","doi":"10.1109/ICTACS56270.2022.9988385","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9988385","url":null,"abstract":"Coronavirus Disease 2019 is occurred as a challenging disease among the scientist worldwide. The disease is developed at an extensive level. Thus, the disease must be detected, reported, isolated, diagnosed and cured at initial phase for mitigating its growth rate. This research paper is conducted on the basisof predicting covid-19 ML algorithms. The methods of predicting this disease consist of diverse stages inwhich data is added as input, pre-processed, attributes are extracted and data is classified. This research work focuses on gathering the authentic dataset which get pre-processed for the classification. In the phase of feature extraction,PCA and k-mean algorithms are applied. The votingclassification method is applied in this work in which GNB, BNB, RF and Support Vector Machine algorithms are integrated. Python is executed to implement the introduced method. Diverse metrics are considered to analyze the outcomes. Using supervised machine learning, we create this model. The branch of ML focuses on implementing intelligent models so that various complicated issues can be tackled. The introduced method offers higher accuracy, precisionand recall in comparison with other classifiers.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"53 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124300512","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

Antenna-Filter Integration for Wireless Applications 无线应用天线滤波器集成

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988430

Shilpam Saxena, Apurva Shrivastava, Sudhanshu Tripathi

引用次数: 0

Implementation and Performance Analysis of Novel Support Vector Machine Classifier for Detecting Eye Cancer Image in comparison with Decision Tree 支持向量机分类器在眼癌图像检测中的应用及性能分析

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9988176

D. R. D. Varma, R. Priyanka

引用次数: 0

Real-time Visual Detection and Tracking is Implemented in a Clustered Environment using an Adaptive Kernel-Supported Correlation Filter Algorithm 利用自适应核支持相关滤波算法在集群环境下实现实时视觉检测和跟踪

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI: 10.1109/ICTACS56270.2022.9987786

T. V. Kumar, F. V. A. Raj, B. Gopinath, B. Suresh, S. Tamizharasi

{"title":"Real-time Visual Detection and Tracking is Implemented in a Clustered Environment using an Adaptive Kernel-Supported Correlation Filter Algorithm","authors":"T. V. Kumar, F. V. A. Raj, B. Gopinath, B. Suresh, S. Tamizharasi","doi":"10.1109/ICTACS56270.2022.9987786","DOIUrl":"https://doi.org/10.1109/ICTACS56270.2022.9987786","url":null,"abstract":"Following moving articles alongside their development through video groupings are perhaps of the most essential and most vital undertaking in PC vision. This fills in as the establishment for various more significant level mechanized applications in various spaces, including observation, expanded reality and movement catch in moving item discovery. Object following is key component of an IVS framework which can additionally be demonstrated for some dubious movement identification frameworks. There are numerous approaches and proposed algorithms for object tracking, but the article proposed Scale Adaptive Kernel Support Correlation Filter Algorithm (SKSCF), which is the basis for the implementation of IVS in this paper. It also derives an equivalent formulation of an SVM model with the circulant matrix expression and presents an effective alternating optimization method for visual tracking. The proposed work characterized to meet following goals: to make a video grouping for moving item following; to plan an exploratory set ready for moving item discovery; and, to plan and carry out moving item following calculation, the proposed calculation was carried out on a caught video succession. Object was identified first as per the picture info, and afterward followed in ensuing casings. The exploratory execution could play out the article following without missing any edge and could effectively overlay bouncing box. It could effectively create a picture grouping after the total execution of Mean Shift Flowchart. The presentation of calculation was checked by effectively following the client characterized object at any climate and playing out the overlay capability in the recognized article.","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132094434","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