2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)最新文献

筛选
英文 中文
Improving the Contrast of Dark Images with Fusion Blending of Fraction-Order Fusion Model and Bright Channel Prior 分数阶融合模型与明亮通道先验融合提高暗图像对比度
Sudeep D. Thepade, Mrunal E. Idhate
{"title":"Improving the Contrast of Dark Images with Fusion Blending of Fraction-Order Fusion Model and Bright Channel Prior","authors":"Sudeep D. Thepade, Mrunal E. Idhate","doi":"10.1109/CENTCON52345.2021.9687991","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9687991","url":null,"abstract":"The photos were taken in the dark light or poor environment always affects the quality of the images as these images are not able to understand for humane eyes and machines for experimental analysis. These images are hard to understand and identify objects with the help of precise details of the images. Sometimes machines get confused about these details of the images as image quality is degraded due to images taken in a poorly illuminated or dark environment. There are many existing techniques available for the contrast enhancement of the images. Some of these techniques have disadvantages. Disadvantages as a blurred image, a noise present in the image, the image gets distorted, etc. to overcome such disadvantages this paper proposed contrast enhancement techniques based on the simple weight blending of the bright channel prior(BCP) and Fraction-Order Fusion Model (FFM). For this experimentation exclusively dark image dataset is used and for the evaluation of the quality of the images entropy values of images are calculated. The outcomes of this experimentation give a better result compared to the individual output of bright channel prior (BCP), Fraction-Order Fusion Model (FFM), and other existing methods.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"7 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":"124187541","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
Dual Band Microstrip 2×8 Array Antenna At Green Flexible RF 绿色柔性射频双波段微带2×8阵列天线
Manasa K R, R. Narendra
{"title":"Dual Band Microstrip 2×8 Array Antenna At Green Flexible RF","authors":"Manasa K R, R. Narendra","doi":"10.1109/CENTCON52345.2021.9687887","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9687887","url":null,"abstract":"5G empowers a novel network that is envisioned to unite all the appliances, machines and gadgets effectively. 5G introduces wide bandwidth with the extension of additional frequency spectrum resources. The 5G network is capable of working both in lower bands like S-band and C-bands and also works in millimetre wave spectrum including Ka-band that helps achieve higher data rate, gain, efficiency and reduced delay. High performance, wideband high gain, compact size and low profile millimetre wave antennas are required for 5G enabled applications to achieve interference free communication. This article presents a microstrip array antenna for millimetre wave applications that resonates in dual bands at green flexible radio frequency range. The antenna array uses parallel feeding technique. The artistic slots introduced in the patches, round and opposite corner fillets result in dual frequency resonance at 57GHz and 60GHz. The proposed small array design with size of 2 × 8 and defected ground results in better gain, directivity, efficiency which is suitable for 5G communication.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"5 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":"126188885","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
Predicting the Soil Suitability using Machine Learning Techniques 利用机器学习技术预测土壤适宜性
Vaishnavi Jayaraman, S. S, K. Monica, Arunraj Lakshminarayanan
{"title":"Predicting the Soil Suitability using Machine Learning Techniques","authors":"Vaishnavi Jayaraman, S. S, K. Monica, Arunraj Lakshminarayanan","doi":"10.1109/CENTCON52345.2021.9688283","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688283","url":null,"abstract":"Agriculture is a detracting sector in the global providence, which is defined as the practice of cultivating crops. Precision agriculture using machine learning algorithms is one of the fast-growing methodologies. It explores the usage of modern technologies to increase the crop yield rate by decreasing the utilization of fertilizers. The main aim of this study is to predict the soil suitability by utilizing the sensors and machine learning techniques. The temperature, humidity, pH and soil moisture were the main sources for plant growth. The nature of the soil would be identified, by measuring the above said entities. This paper analyses the soil suitability using diversified machine learning techniques such as KNN, Support Vector Machine, Random Forest, Naive Bayes, and Extreme Learning Machine. ELM model predicts the soil suitability with 99% of accuracy.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"10 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":"121529266","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
An Encryption Method Involving Homomorphic Transform 一种涉及同态变换的加密方法
Ankit Vishnoi, A. Aggarwal, A. Prasad, M. Prateek
{"title":"An Encryption Method Involving Homomorphic Transform","authors":"Ankit Vishnoi, A. Aggarwal, A. Prasad, M. Prateek","doi":"10.1109/CENTCON52345.2021.9688040","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688040","url":null,"abstract":"Data security is an important aspect for datasets of every size and type. Data security refers to provide a secure environment to datasets, web-based datasets, and preventing unauthorized access to the data. The key data security technique is encryption, where the digital data is encrypted. As result, the unauthorized person or hacker gets unreadable data. The computing process generates data that is encrypted by the key and can be decrypted with the correct key only. In this research, an approach is proposed of using transforms to provide a better cryptography process to secure data even during communication. The result of the proposed method indicates that in any condition, the ciphertext will always be the same for each input, but the encryption key will change each time, which makes this encryption complex to break","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"1 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":"129844573","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: 4
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信