Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819813
S. D’souza, Kavita Sonawane
Sentiment is an attitude, thought, or judgment prompted by feeling. Sentiment Analysis can be defined as the process of analyzing online pieces of writing to determine the emotional tone they carry. With the vast growth of the social media content on the Internet in the past few years, people now express their opinion on almost anything in discussion. With respect to this, Bag–of–Words (BoW) is the most popular way to model text in statistical machine learning (ML) approaches. However, the performance of BoW sometimes remains unlimited due to some fundamental deficiencies in handling the polarity shift problem and other few challenges like quality of the opinions, hidden state representations, polarity categorization etc. To come across these challenges our focus will be on Dual Sentiment Analysis which processes the Sentiment with all the perspectives (positive, negative or neutral). This may lead towards the accurate prediction for final decision making based on the reviews given by the customers. The proposed work is being experimented on the Amazon Product reviews specifically the Mobile device reviews. This work aims at overcoming the limitation of existing system and improving the accuracy.
{"title":"Sentiment Analysis Based on Multiple Reviews by using Machine learning approaches","authors":"S. D’souza, Kavita Sonawane","doi":"10.1109/ICCMC.2019.8819813","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819813","url":null,"abstract":"Sentiment is an attitude, thought, or judgment prompted by feeling. Sentiment Analysis can be defined as the process of analyzing online pieces of writing to determine the emotional tone they carry. With the vast growth of the social media content on the Internet in the past few years, people now express their opinion on almost anything in discussion. With respect to this, Bag–of–Words (BoW) is the most popular way to model text in statistical machine learning (ML) approaches. However, the performance of BoW sometimes remains unlimited due to some fundamental deficiencies in handling the polarity shift problem and other few challenges like quality of the opinions, hidden state representations, polarity categorization etc. To come across these challenges our focus will be on Dual Sentiment Analysis which processes the Sentiment with all the perspectives (positive, negative or neutral). This may lead towards the accurate prediction for final decision making based on the reviews given by the customers. The proposed work is being experimented on the Amazon Product reviews specifically the Mobile device reviews. This work aims at overcoming the limitation of existing system and improving the accuracy.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128592502","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819630
M. Thushara, Tadi Mownika, Ritika Mangamuru
Growth in the number of research documents getting published is increasing. Finding a research document under interested domain by referring the whole paper has become a tedious task. Keywords, Keyphrases gives the summary of the text. Keywords and keyphrases help in understanding the information described in the research document. The domain of a research document can be determined based on the keywords and keyphrases extracted. Extracting keywords and keyphrases manually is a tedious task. Automatic keyphrase extraction techniques help in overcoming this challenging task. This paper is a comparative study of unsupervised keyphrase extraction algorithms without using corpus. It compares the performance of PositionRank which considers the position of the all words occurrences in the document with TextRank and RAKE (Rapid Automatic Keyword Extraction).
{"title":"A Comparative Study on different Keyword Extraction Algorithms","authors":"M. Thushara, Tadi Mownika, Ritika Mangamuru","doi":"10.1109/ICCMC.2019.8819630","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819630","url":null,"abstract":"Growth in the number of research documents getting published is increasing. Finding a research document under interested domain by referring the whole paper has become a tedious task. Keywords, Keyphrases gives the summary of the text. Keywords and keyphrases help in understanding the information described in the research document. The domain of a research document can be determined based on the keywords and keyphrases extracted. Extracting keywords and keyphrases manually is a tedious task. Automatic keyphrase extraction techniques help in overcoming this challenging task. This paper is a comparative study of unsupervised keyphrase extraction algorithms without using corpus. It compares the performance of PositionRank which considers the position of the all words occurrences in the document with TextRank and RAKE (Rapid Automatic Keyword Extraction).","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123217021","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819850
P. Apoorva, H. C. Impana, S. Siri, M. Varshitha., B. Ramesh
This paper presents a real time face recognition using a automated surveillance camera. The proposed system consists of 4 steps, including (1)training of real time images (2)face detection using Haar-classifier (3) comparison of trained real time images with images from the surveillance camera (4)result based on the comparison. An important application of interest is automated surveillance, where the objective is to recognize people who are on a watch list. The aspiration of this paper is to compare an image with several images which has been already trained. In this paper, we represent a methodology for face detection robustly in real time environment. Haar cascading is one of the algorithm for face detection. Here we use Haar like classifiers to track faces on OpenCV platform. The accuracy of the face recognition is very high. The proposed system can successfully recognize more than one face which is useful for quickly searching suspected persons as the computation time is very low. In India, we have a system for recognizing citizen called Aadhaar. If we use this as a citizenship database we can differentiate between citizen and foreigner and further investigate whether the identified person is criminal or not.
{"title":"Automated Criminal Identification by Face Recognition using Open Computer Vision Classifiers","authors":"P. Apoorva, H. C. Impana, S. Siri, M. Varshitha., B. Ramesh","doi":"10.1109/ICCMC.2019.8819850","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819850","url":null,"abstract":"This paper presents a real time face recognition using a automated surveillance camera. The proposed system consists of 4 steps, including (1)training of real time images (2)face detection using Haar-classifier (3) comparison of trained real time images with images from the surveillance camera (4)result based on the comparison. An important application of interest is automated surveillance, where the objective is to recognize people who are on a watch list. The aspiration of this paper is to compare an image with several images which has been already trained. In this paper, we represent a methodology for face detection robustly in real time environment. Haar cascading is one of the algorithm for face detection. Here we use Haar like classifiers to track faces on OpenCV platform. The accuracy of the face recognition is very high. The proposed system can successfully recognize more than one face which is useful for quickly searching suspected persons as the computation time is very low. In India, we have a system for recognizing citizen called Aadhaar. If we use this as a citizenship database we can differentiate between citizen and foreigner and further investigate whether the identified person is criminal or not.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116198898","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819692
Ruchi Sharma, K. Davuluri
The aim of this paper is detecting and analyzing design patterns and architectural patterns for two software applications that use Machine Learning (ML) and Deep Learning techniques respectively. The classification is done based on the design principles that need to be adhered for a standard design and architectural patterns. ML based applications generally have ubiquitous modules to some extent. However, modeling their components through varied design patterns bring out positive changes to the performance of the systems as well as mitigates many of the computational shortcomings faced otherwise. Although it is still a novel approach for systems implementing machine learning algorithms, the paper aims to bring a new paradigm in analyzing system models.
{"title":"Design patterns for Machine Learning Applications","authors":"Ruchi Sharma, K. Davuluri","doi":"10.1109/ICCMC.2019.8819692","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819692","url":null,"abstract":"The aim of this paper is detecting and analyzing design patterns and architectural patterns for two software applications that use Machine Learning (ML) and Deep Learning techniques respectively. The classification is done based on the design principles that need to be adhered for a standard design and architectural patterns. ML based applications generally have ubiquitous modules to some extent. However, modeling their components through varied design patterns bring out positive changes to the performance of the systems as well as mitigates many of the computational shortcomings faced otherwise. Although it is still a novel approach for systems implementing machine learning algorithms, the paper aims to bring a new paradigm in analyzing system models.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121676421","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}
Bodo language is a relatively low resource language. Other than the text-book, novels and some print publication of newspaper, there appears to be very few resources available in the public domain. As the technology becomes affordable there is a growing number of active Bodo internet users. It requires a technology that can bring information in their own language. Machine translation appears to be a promising solution for that purpose. In this work we build an English-Bodo Neural Machine Translation by adopting a two layered bidirectional Long Short Term Memory (LSTM) cells that can capture the long term dependencies. As very few work has been done on English-Bodo NMT, we make our baseline model which produced a BLEU Score of 11.8 . We then gradually overcome the baseline model by introducing several attention mechanism. We achieved a BLEU Score of 16.71 using the approach presented in Bahdanu. Furthermore we got a better BLEU score of 17.9 when we introduced beam search with a beam width of 5. We found that the model performs very well despite the few dataset available.
博多语是一种资源相对较低的语言。除了教科书、小说和一些报纸的印刷出版物外，在公共领域可以获得的资源似乎很少。随着这项技术变得负担得起，活跃的Bodo互联网用户越来越多。它需要一种能够用他们自己的语言传递信息的技术。机器翻译似乎是一个很有前途的解决方案。在这项工作中，我们通过采用两层双向长短期记忆(LSTM)细胞来捕获长期依赖关系，构建了一个英语- bodo神经机器翻译。由于在英语- bodo NMT上做的工作很少，我们建立了基线模型，该模型产生了11.8的BLEU分数。然后，我们通过引入几种注意机制来逐步克服基线模型。使用Bahdanu提出的方法，我们获得了16.71的BLEU评分。此外，当我们引入波束宽度为5的波束搜索时，我们获得了17.9的更好的BLEU分数。我们发现，尽管可用的数据集很少，但该模型表现非常好。
{"title":"Attention based English-Bodo Neural Machine Translation System for Tourism Domain","authors":"Sanjib Narzary, Maharaj Brahma, Bobita Singha, Rangjali Brahma, Bonali Dibragede, Sunita Barman, Sukumar Nandi, Bidisha Som","doi":"10.1109/ICCMC.2019.8819699","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819699","url":null,"abstract":"Bodo language is a relatively low resource language. Other than the text-book, novels and some print publication of newspaper, there appears to be very few resources available in the public domain. As the technology becomes affordable there is a growing number of active Bodo internet users. It requires a technology that can bring information in their own language. Machine translation appears to be a promising solution for that purpose. In this work we build an English-Bodo Neural Machine Translation by adopting a two layered bidirectional Long Short Term Memory (LSTM) cells that can capture the long term dependencies. As very few work has been done on English-Bodo NMT, we make our baseline model which produced a BLEU Score of 11.8 . We then gradually overcome the baseline model by introducing several attention mechanism. We achieved a BLEU Score of 16.71 using the approach presented in Bahdanu. Furthermore we got a better BLEU score of 17.9 when we introduced beam search with a beam width of 5. We found that the model performs very well despite the few dataset available.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121845202","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}
Internet of Things is the emerging technology which evolves drastically in all the domains like industries, medicine, companies, house hold appliances, smart devices etc.,. In a bit further IoT technology started to proliferate its hybrid applications particularly in the area of image processing. The increasing integration of IoT devices and the smart sensors helps in reorganizing the face of a person for a better results and security purpose. In our research we detect the pictures of the people and we observe the mentality of the person in different mechanisms. Basically computer version is a considered as one of the very complicated domains. For such domains we have to adapt the process of automatic or semiautomatic mechanisms without any user interaction. Our proposed task will show all kind of possible methods for performing the better results. In his research work, we use pictures with sensors that utilizes the capabilities and principles of IoT.
{"title":"A Face Recognition Method in the IoT for Security Appliances in Smart Homes, offices and Cities","authors":"Abhishek Kumar, Palvadi Srinivas Kumar, Rashmi Agarwal","doi":"10.1109/ICCMC.2019.8819790","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819790","url":null,"abstract":"Internet of Things is the emerging technology which evolves drastically in all the domains like industries, medicine, companies, house hold appliances, smart devices etc.,. In a bit further IoT technology started to proliferate its hybrid applications particularly in the area of image processing. The increasing integration of IoT devices and the smart sensors helps in reorganizing the face of a person for a better results and security purpose. In our research we detect the pictures of the people and we observe the mentality of the person in different mechanisms. Basically computer version is a considered as one of the very complicated domains. For such domains we have to adapt the process of automatic or semiautomatic mechanisms without any user interaction. Our proposed task will show all kind of possible methods for performing the better results. In his research work, we use pictures with sensors that utilizes the capabilities and principles of IoT.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132375391","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819720
Uvais Karni, S. S. Ramachandran, Kalpathy Sivaraman, A. K. Veeraraghavan
In this contemporary world, the number of accidents occurring has increased drastically which leads to an increase in the number of fatal deaths. This is mostly caused by the distractions that driver encounters. For example, texting and driving,less attention span of driver,etc. Due to the above reasons, autonomous cars would be a better option which takes the errors of a driver away from the equation. The proposed concept in the paper is to make an autonomous downscaled model car using a generic RC car as base. We aim to achieve the above by using image processing which is trained by using neural networks to create a model through which autonomous cars are achieved. The hardware components used in this project are Ras pberry PI 3 B microcomputer , camera module, HCSR04 ultrasonic sensor. We achieve the following features in our model, (a)Lane detection, (b)Traffic signal identification, (c)Road signs identification, (d)Obstacle detection avoidance, (e)Pedestrian Detection.
在当今世界，发生的事故数量急剧增加，导致致命死亡人数增加。这主要是由于司机遇到的干扰造成的。比如，边开车边发短信，司机注意力不集中等等。由于上述原因，自动驾驶汽车将是一个更好的选择，它可以消除驾驶员的错误。本文提出的概念是以通用的RC车为基础，制造一辆自动驾驶的微缩模型车。我们的目标是通过使用图像处理来实现上述目标，图像处理通过使用神经网络来训练，从而创建一个模型，通过该模型实现自动驾驶汽车。本课题所使用的硬件组件有Ras berry PI 3b微型计算机、摄像模块、HCSR04超声波传感器。我们在我们的模型中实现了以下特征，(a)车道检测，(b)交通信号识别，(c)道路标志识别，(d)障碍物检测避免，(e)行人检测。
{"title":"Development Of Autonomous Downscaled Model Car Using Neural Networks And Machine Learning","authors":"Uvais Karni, S. S. Ramachandran, Kalpathy Sivaraman, A. K. Veeraraghavan","doi":"10.1109/ICCMC.2019.8819720","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819720","url":null,"abstract":"In this contemporary world, the number of accidents occurring has increased drastically which leads to an increase in the number of fatal deaths. This is mostly caused by the distractions that driver encounters. For example, texting and driving,less attention span of driver,etc. Due to the above reasons, autonomous cars would be a better option which takes the errors of a driver away from the equation. The proposed concept in the paper is to make an autonomous downscaled model car using a generic RC car as base. We aim to achieve the above by using image processing which is trained by using neural networks to create a model through which autonomous cars are achieved. The hardware components used in this project are Ras pberry PI 3 B microcomputer , camera module, HCSR04 ultrasonic sensor. We achieve the following features in our model, (a)Lane detection, (b)Traffic signal identification, (c)Road signs identification, (d)Obstacle detection avoidance, (e)Pedestrian Detection.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130211180","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819665
D. Sucharitha, N. Prudhvi Raj, R. Sravya, Sudheer Raja Venishetty
In this paper, Hamming code encoder and decoder circuit is designed based on Gate Diffusion Input (GDI) logic to achieve error free transmission and reception in digital data communication. GDI logic is a new technique used for designing low power VLSI circuits. This technique provides better trade-off between power, delay and area compared to other logic styles existing in the literature, while maintaining low complexity of the circuit. Hamming code encoder and decoder circuit architectures are developed using GDI technique and are simulated in gpdk 130 nm technology using Mentor Graphics® EDA tool. The advantages of GDI technique is reported in this paper in comparison to architectures developed using CMOS logic styles.
{"title":"GDI Logic Based Design of Hamming-Code Encoder and Decoder for Error Free Data Communication","authors":"D. Sucharitha, N. Prudhvi Raj, R. Sravya, Sudheer Raja Venishetty","doi":"10.1109/ICCMC.2019.8819665","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819665","url":null,"abstract":"In this paper, Hamming code encoder and decoder circuit is designed based on Gate Diffusion Input (GDI) logic to achieve error free transmission and reception in digital data communication. GDI logic is a new technique used for designing low power VLSI circuits. This technique provides better trade-off between power, delay and area compared to other logic styles existing in the literature, while maintaining low complexity of the circuit. Hamming code encoder and decoder circuit architectures are developed using GDI technique and are simulated in gpdk 130 nm technology using Mentor Graphics® EDA tool. The advantages of GDI technique is reported in this paper in comparison to architectures developed using CMOS logic styles.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130467333","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819753
Priti Chittekar, Smita Deshmukh
Multiple copies of URLs gathered by the web crawlers responsible for pages with similar or near about to similar content. Few pages combined by the web crawlers consist of similar content. Different URLs with Similar Text are generally known as DUST. Result of this is crawl data, to store the data and use such duplicated data results in building of less quality marking, waste of resources and destitute naive user experiences.To study with such problem, multiple studies have been observed. Previous studies focus only on URL based DUST removal .The proposed method removes content depended DUST and URL based DUST. To crawl the documents we are using a new method of metacrawler which fetches results from three Search engine. We are going to compare each website content with the other linked content to remove duplicates using k- gram paraphrased technique.
{"title":"Analysis of Metacrawler approach for URL based DUST removal by knowledge engineering systems","authors":"Priti Chittekar, Smita Deshmukh","doi":"10.1109/ICCMC.2019.8819753","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819753","url":null,"abstract":"Multiple copies of URLs gathered by the web crawlers responsible for pages with similar or near about to similar content. Few pages combined by the web crawlers consist of similar content. Different URLs with Similar Text are generally known as DUST. Result of this is crawl data, to store the data and use such duplicated data results in building of less quality marking, waste of resources and destitute naive user experiences.To study with such problem, multiple studies have been observed. Previous studies focus only on URL based DUST removal .The proposed method removes content depended DUST and URL based DUST. To crawl the documents we are using a new method of metacrawler which fetches results from three Search engine. We are going to compare each website content with the other linked content to remove duplicates using k- gram paraphrased technique.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134208203","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}
Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819731
Kalyani S. Ulabhaje, Meenakshi S. Arya
The merging of images obtained by satellites through remote sensing has evolved into an established protocol. In popular parlance such blending is known as image fusion. This is done chiefly because it gives myriad advantages. Image fusion comes in extremely useful in the observation, study and analysis of diverse fields, including environment, agriculture and other related areas. In essence, what happens in image fusion is that the needed data or information is gleaned from numerous images. These images then are coalesced to form fewer pictures. The ideal, of course, is the blending of them into a lone picture. This is highly sought-after because the image thus intermingled is said to contain all relevant data and, moreover, is more suitable and error-free than an image secured from one single source. Needless to say, it also incorporates all the information that is needed. Besides this, there are other benefits. For one, it curtails the volume of data. For another, it produces images that are pertinent and apt. This paper’s chief objective is to proffer a suggested methodology on the fusion between the capabilities of optical and microwave satellite images and to improve the visible quality of Landsat image.
{"title":"A Proposed Methodology for the Fusion of Microwave and Optical Remote Sensing Data","authors":"Kalyani S. Ulabhaje, Meenakshi S. Arya","doi":"10.1109/ICCMC.2019.8819731","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819731","url":null,"abstract":"The merging of images obtained by satellites through remote sensing has evolved into an established protocol. In popular parlance such blending is known as image fusion. This is done chiefly because it gives myriad advantages. Image fusion comes in extremely useful in the observation, study and analysis of diverse fields, including environment, agriculture and other related areas. In essence, what happens in image fusion is that the needed data or information is gleaned from numerous images. These images then are coalesced to form fewer pictures. The ideal, of course, is the blending of them into a lone picture. This is highly sought-after because the image thus intermingled is said to contain all relevant data and, moreover, is more suitable and error-free than an image secured from one single source. Needless to say, it also incorporates all the information that is needed. Besides this, there are other benefits. For one, it curtails the volume of data. For another, it produces images that are pertinent and apt. This paper’s chief objective is to proffer a suggested methodology on the fusion between the capabilities of optical and microwave satellite images and to improve the visible quality of Landsat image.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133960517","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}
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