2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)最新文献_第6页

Survey on Automated Aquponics Based Gardening Approaches 基于自动化水培法的园艺方法综述

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473155

K. Aishwarya, M. Harish, S. Prathibhashree, K. Panimozhi

引用次数: 10

Designing and Implementation of Chemical Mixing and Filling Bottles Using PLC 化工混合灌装瓶的PLC设计与实现

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473096

Prasad Birmole, M. Kamble, Sayali Naik, Anjali Sadamate, Heenali. V. Korgaonkar

引用次数: 4

A New Method for Detection of Phishing Websites: URL Detection 一种新的网络钓鱼网站检测方法:URL检测

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473085

Shraddha Parekh, D. Parikh, Srushti Kotak, Prof Smita Sankhe

引用次数: 56

Classification of Hand Gestures from Wearable IMUs using Deep Neural Network 基于深度神经网络的可穿戴imu手势分类

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473301

Karush Suri, Rinki Gupta

引用次数: 5

Gabor filter based Image segmentation for Disease Detection using VHDL 基于Gabor滤波的VHDL疾病检测图像分割

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473083

P. Nagabushanam, S. Radha, Sushmita Selvadass, Kezia Kanishka Joseph

引用次数: 1

A Faster Technique on Rice Disease Detectionusing Image Processing of Affected Area in Agro-Field 基于田间病区图像处理的水稻病害快速检测技术

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473322

Taohidul Islam, M. Sah, S. Baral, Rudra RoyChoudhury

{"title":"A Faster Technique on Rice Disease Detectionusing Image Processing of Affected Area in Agro-Field","authors":"Taohidul Islam, M. Sah, S. Baral, Rudra RoyChoudhury","doi":"10.1109/ICICCT.2018.8473322","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473322","url":null,"abstract":"Plant disease is defined as an abnormal physiological process that distorts the plant's normal structure, growth and function. Disease reduces quality as well as quantity of the crops which in turn affects the economy of country like Bangladesh where agriculture is the main occupation. Since Rice is the major crop, classification of disease in paddy is very important as it prevents the losses in the yields and quantity. Classification of rice disease includes visually observable patterns and color of the affected portion. Manual observation of patterns and colors to classify the diseases require excessive work and appears to be less useful while dealing with non-native diseases. This paper presents a new technique to detect and classify the diseases based on percentage of RGB value of the affected portion using image processing. Once the percentage of RGB from the affected region is extracted and grouped into various classes, they are fed to a simple classifier called Naive Bayes which classifies the disease into various categories. This technique has successfully detected and identified three rice diseases namely rice brown spot, rice bacterial blight, and rice blast. This technique is efficient and faster because it uses only one feature i.e. RGB values of the affected portion which requires minimum computation time to identify and classify the diseases. Rather than processing the whole leaf, this technique even successfully detects the diseases using only a small sample of leaf containing the affected portion for rice disease.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116956246","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: 64

Handwritten Character Recognition Using Deep-Learning 使用深度学习的手写字符识别

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-20 DOI: 10.1109/ICICCT.2018.8473291

Rohan Vaidya, D. Trivedi, Sagar Satra, Prof. Mrunalini Pimpale

引用次数: 34

Ethiopian Banknote Recognition and Fake Detection Using Support Vector Machine 基于支持向量机的埃塞俄比亚纸币识别与假币检测

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-01 DOI: 10.1109/ICICCT.2018.8473013

Mr. Engdaw Ayalew Tessfaw, Mr. Bhupendra Ramani, Mr. Tadesse Kebede Bahiru

{"title":"Ethiopian Banknote Recognition and Fake Detection Using Support Vector Machine","authors":"Mr. Engdaw Ayalew Tessfaw, Mr. Bhupendra Ramani, Mr. Tadesse Kebede Bahiru","doi":"10.1109/ICICCT.2018.8473013","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473013","url":null,"abstract":"Currency recognition is an important task in numerous automated payment services and used to categorize the banknotes of different nation. The importance of automatic methods for currency recognition has been increasing in the time being because of circulation of fake notes is increased in today's economy. This recognition system contains basic image processing techniques such like image acquisition, image preprocesses, extract features and classification using support vector machine. Basically camera or scanner used for image acquisition. The images of currency processed using a variety of preprocessing techniques and different features of the image extracted using local binary pattern technique, once the features are extracted it is important to recognize the currency using effective classifier called Support vector machine and Finally a prototype able to recognize Ethiopian paper currency with accuracy of 98% shows high performance classification model for paper currency recognition and also verify the validity of given banknotes with average accuracy of 93% rate.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114677357","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: 13

Security Enhanced Medical Data Server for Cardiac Arrest Care Analysis Using DNSSEC 使用DNSSEC进行心脏骤停护理分析的安全性增强医疗数据服务器

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-01 DOI: 10.1109/ICICCT.2018.8473330

M. Shobeetha, A. Shaik Abdul Khadir

引用次数: 0

Visualization of News Feed Data using Lexicon-based Approach 使用基于词典的方法可视化新闻Feed数据

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) Pub Date : 2018-04-01 DOI: 10.1109/ICICCT.2018.8473244

Pujitha Appasani, M. Latha

引用次数: 0