2022 6th International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第5页

Intelligent Adaptive Anisotropic Diffusion Filtered Deep Neural Network With Gaussian Activation For Image Classification 基于高斯激活的智能自适应各向异性扩散滤波深度神经网络图像分类

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753971

G. Praveenkumar, R. Nagaraj

{"title":"Intelligent Adaptive Anisotropic Diffusion Filtered Deep Neural Network With Gaussian Activation For Image Classification","authors":"G. Praveenkumar, R. Nagaraj","doi":"10.1109/ICCMC53470.2022.9753971","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753971","url":null,"abstract":"This paper presents a novel adaptive anisotropic diffusion filtered deep neural network (AADF-DNN) model for achieving effective image classification with increase the accuracy and reduces the running time, false-positive ratio. The proposed AADF-DNN model uses deep learning and Gaussian activation function to reduce the false-positive ratio. First, a number of input images are given to the input layer get pre-processed by adaptive anisotropic diffusion filtered reducing the noise. Then, the input layer sends the input images into hidden layers. The hidden layer is used to extract significant features such as shape, color, texture, and size for reducing the running time. Next, the Gaussian activation function is used to classify the images into corresponding classes based on the measurement value between the extracted features and pre-stored features. Finally, the classification results of input images are obtained. Experimental results illustrate that the AADF-DNN model enhances the classification of image performance with higher accuracy at the minimal running time than compared to the PCGRBM.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116025170","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

Designing an IoT based Kitchen Monitoring and Automation System for Gas and Fire Detection 设计一个基于物联网的厨房监控和自动化系统，用于燃气和火灾探测

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754118

L. M, J. J. Jeya Sheela M.E

{"title":"Designing an IoT based Kitchen Monitoring and Automation System for Gas and Fire Detection","authors":"L. M, J. J. Jeya Sheela M.E","doi":"10.1109/ICCMC53470.2022.9754118","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754118","url":null,"abstract":"The kitchen is among the highly crucial rooms in any home. While working in the kitchen, many safety precautions must be performed. An uncontrolled fire, an excessive rise in temperatures, the existence of leaking gas, and other factors can all contribute to surprise explosions. The explosions must be spotted and, cleared as soon as possible. The paper's principle goal is to discover and, remedy kitchen safety concerns. When there is a significant rise in leakages, the Sensor senses it and, the exhaust system turns on, the alarm goes on, when the gas level surpasses the recommended amount. It also automatically shuts down the supply of gas. Even, the information is notified to the users' mobile phone, by the app. Additionally, many Fire detecting systems are deployed in this system, to detect the fire. In the event of a fire, it senses it and, immediately sprays water to shut off the flic and, shut off the Gas supply. When the temperature is high in the kitchen, it ventilates it by exhaust system, thus by dropping the room temperature. It even uses a PIR sensor, to inspect for signs of a person, in the kitchen. Finally, this technology can be deployed to automate the kitchen, allowing users to utilize the kitchen equipment. All of these controls and, the information is accessed using the Blynk app, which can be accessed by smart phones. This solution is envisioned to increase home Protection, in the Kitchen, along with to automate your kitchen and, daily tasks for senior users.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121960731","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

Natural Language Processing based Automated Essay Scoring with Parameter-Efficient Transformer Approach 基于自然语言处理的参数有效转换方法自动作文评分

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753760

Angad Sethi, Kavinder Singh

引用次数: 7

Security Analysis of Rural Sports Consumption Upgrade Based on Cloud Payment and Blockchain 基于云支付和b区块链的农村体育消费升级安全性分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754102

Bin Feng, Ke Xu, Lisha Chen

引用次数: 0

Neural Computing and Data Fusion Modeling Analysis of the Index System of China's Industrial Modernization Level 中国工业现代化水平指标体系的神经计算与数据融合建模分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753700

ChangChun Yan, Jiajia Zhang

引用次数: 0

Comparative Analysis of Banana Leaf Disease Detection and Classification Methods 香蕉叶片病害检测与分类方法的比较分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753840

N. B. Raja, P. Selvi Rajendran

{"title":"Comparative Analysis of Banana Leaf Disease Detection and Classification Methods","authors":"N. B. Raja, P. Selvi Rajendran","doi":"10.1109/ICCMC53470.2022.9753840","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753840","url":null,"abstract":"Agriculture, along with its related industries, is without a doubt India’s largest source of income. Plant disease is a major concern in agriculture today, as it decreases food production and quality. Plant diseases, that are previously infected, microbes, fungus, roundworms, and nutrient deficiency, inflict significant damage to crops and have the following consequences: lower crop yield and quality. It also kills the plant, reduces the farmer’s profits, and raises the cost of production throughout the control period. The banana is the most important fruit in Pacific and the Asia. The banana plant was susceptible to several ailments, the effects of that can be seen on the leaves. The infections would be Streak Virus, yellow Sigatoka, Panama, Black Sigatoka, and Banana Bunchy Top Virus. As a result, early detection of plant diseases is important. These researches greatly focus on Deep learning algorithms. In this study, huge potential efforts are made to study the complete background of banana disease detection. In the end, this study also highlights a comparison of recent research directions in banana leaf disease detection using various classification methods.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128752500","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: 2

Hybrid Energy Dual Storage Systems for EV Powertrain with Enhanced Algorithm GOA and GA 基于改进算法GOA和GA的电动汽车动力总成混合能量双存储系统

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754001

B. Pattanaik, Mukil Alagirisamy

{"title":"Hybrid Energy Dual Storage Systems for EV Powertrain with Enhanced Algorithm GOA and GA","authors":"B. Pattanaik, Mukil Alagirisamy","doi":"10.1109/ICCMC53470.2022.9754001","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754001","url":null,"abstract":"Although EV offers several advantages such as being terrain friendly, producing less noise, and reducing dependency on reactive powers, it also has significant drawbacks. High power and high energy force systems for EVs will be obtained concurrently through the integration of batteries and ultra-capacitors. As a result, ultra-capacitors manage short-term power demands, while batteries provide long-term mobility for the vehicle. A novel algorithm, cold-thoroughbred GOA-GA, is proposed by combining the GOA and GA. The proposed hybrid GOA-GA has a strong eventuality to escape original optima while achieving the convergence. The proposed crossbred algorithm is used to perform a multi-objective function optimization to drop the HESS mass as well as increase the vehicle's operating range. By exercising the MATLAB/ Goad software, the entire frame was erected with the FTP-75, US06 (maximum speed as well as demanded acceleration) and HWFET driving cycles. When compared to an equivalent EV posted with a single HESS unit, the proposed binary-HESS armature has increased driving range while lowering the HESS mass.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129838419","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

Quasi-Oppositional Satin Bowerbird with Deep Learning based Content based Image Retrieval 基于深度学习的拟对立缎面园丁鸟图像检索

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754135

D. P. Singh, Susheel George Joseph, V. Selvi, S. Karunakaran, A. G., B. Jegajothi

{"title":"Quasi-Oppositional Satin Bowerbird with Deep Learning based Content based Image Retrieval","authors":"D. P. Singh, Susheel George Joseph, V. Selvi, S. Karunakaran, A. G., B. Jegajothi","doi":"10.1109/ICCMC53470.2022.9754135","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754135","url":null,"abstract":"Content-based image retrieval (CBIR) is commonly employed to retrieve images from a massive set of unlabeled images. The design of CBIR model faces several limitations, as it is mainly based on the extraction of image features to calculate the similarity amongst the query image (QI) and database images. The recent advances of deep learning (DL) models help to attain remarkable retrieval outcomes. In this view, this paper presents a novel quasi-oppositional satin bowerbird optimizer with Densely Connected Networks (QOSBO-DCN) for CBIR. The proposed QOSBO-DCN technique aims to properly retrieve the images related to the QI in an effective and automated manner. The proposed QOSBO-DCN technique derives a DenseNet-77 model as a feature extractor to derive feature vectors from the QI and database images. Besides, the QOSBO algorithm is utilized to adjust the hyperparameter values of the DenseNet-77 model in such a way that the retrieval performance can be improved. Additionally, Euclidean distance is used as a similarity measurement approach to determine the highly resembling images and retrieve them. The simulation analysis of the QOSBO-DCN technique is performed using Corel10K dataset and the results reported the betterment of the QOSBO-DCN technique over the existing techniques.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127343371","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: 3

A Study on Brain Tumor Analysis Using Deep Learning Methods 基于深度学习方法的脑肿瘤分析研究

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753979

Sheetal Prusty, Rutuparna Panda, Lingraj Dora, S. Agrawal

引用次数: 1

Plant Disease Identification and Suggestion of Remedial Measures using Machine Learning 基于机器学习的植物病害识别及补救措施建议

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754011

Shyam Chand G, H. R.

引用次数: 0