2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)最新文献_第10页

A Hybrid Network Based on GAN and CNN for Food Segmentation and Calorie Estimation 基于GAN和CNN的食物分割和卡路里估计混合网络

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760831

R. Jaswanthi, E. Amruthatulasi, Ch. Bhavyasree, Ashutosh Satapathy

{"title":"A Hybrid Network Based on GAN and CNN for Food Segmentation and Calorie Estimation","authors":"R. Jaswanthi, E. Amruthatulasi, Ch. Bhavyasree, Ashutosh Satapathy","doi":"10.1109/ICSCDS53736.2022.9760831","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760831","url":null,"abstract":"Calories play an essential role in health aspects that lead to diseases like coronary heart disease, liver disease, cancer, and cholesterol. A study from 2020 reported that globally, overweight adults outnumber underweight individuals by more than 1.9 billion, while obese adults outnumber underweight ones by 650 million. Statistics from India show that abdominal obesity is the most significant risk factor, and it varies from 16.9% to 36.3%. Deep learning is an advanced image processing technology that solves problems and ensures food challenges because deeper networks have a better ability to process many features in an image. In our study, we propose a hybrid framework to predict the calorie content of food items on a plate. This includes three main parts: segmentation to segment the food from the image, image classification for classifying the food items, and calculating the calories present in those food items. A generative adversarial network is used for the segmentation, while a convolutional neural network is used for the classification and calorie estimation. The above models trained on the food images from the UNIMIB 2016 dataset have correctly recognized and estimated the calories of a food item with an accuracy of 95.21%.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127355939","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: 5

Grey Wolf Optimization based BICMB-OFDM for millimeter wave Massive MIMO systems 基于灰狼优化的BICMB-OFDM毫米波海量MIMO系统

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760802

J. Friska, M. N. Jenefa

引用次数: 0

Intelligent Capture and Analysis of Data Stream Images of Rural E-Commerce Live Broadcast Platform based on Deep Stochastic Neural Network 基于深度随机神经网络的农村电商直播平台数据流图像智能采集与分析

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760869

Xiang. Cao

引用次数: 0

Research on Intelligent Parsing of Business English Semantics based on Root Data Network Mining 基于根数据网络挖掘的商务英语语义智能解析研究

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9761032

Wenpu Wang, Wei-Ting Lin

引用次数: 0

Survey on Intrusions Detection System using Deep learning in IoT Environment 物联网环境下基于深度学习的入侵检测系统研究

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760993

B. R, S. Deepajothi, Prabaharan G, Daniya T, P. Karthikeyan, V. S

引用次数: 4

Robot Step Length Automatic Control Method based on Virtual Reality Technology 基于虚拟现实技术的机器人步长自动控制方法

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760867

L. Yang

引用次数: 0

Multi-Neuron Functional Link Artificial Neural Network: A Novel Architecture and its Performance for Wind Energy Prediction 多神经元功能链接人工神经网络:一种风能预测的新架构及其性能

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760812

S. K. Barik, Srikanta Mohapatra, Subhra Debdas

{"title":"Multi-Neuron Functional Link Artificial Neural Network: A Novel Architecture and its Performance for Wind Energy Prediction","authors":"S. K. Barik, Srikanta Mohapatra, Subhra Debdas","doi":"10.1109/ICSCDS53736.2022.9760812","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760812","url":null,"abstract":"In this paper, a novel architecture, multi-neuron functional link artificial neural network (MNFLANN), has been proposed and its performance in predicting wind energy is compared with the other conventional network models, i.e. ANN, multi-layer perceptrons (MLP) and functional link artificial neural networks (FLANN). The name, i.e. MNFLANN is given as per its structure which consists of multiple neurons unlike the conventional FLANN that consists of only one neuron in the output layer. The real-time wind energy data of October month of recent three years from Sotavento wind farm located in Spain has been taken into consideration to evaluate the performance of MNFLANN. Results show that the mean absolute percentage error (MAPE) during testing is so less, i.e. -1.32% for MNFLANN, compared to other conventional architectures, i.e. -9.47% for ANN, - 8.44% for MLP and 15.19% for FLANN. The proposed MNFLANN architecture effectively handles the nonlinearity in input data compared to other conventional architectures due to its improved structure.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128407430","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

ET-RF based Model for Detection of Distributed Denial of Service Attacks 基于ET-RF的分布式拒绝服务攻击检测模型

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760938

V. Gaur, R. Kumar

引用次数: 1

ISFF Based Optimal Route Selection and QoS Enhancement in VANETs 基于ISFF的vanet最优路由选择与QoS增强

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760786

S. S, J. S. Raj

{"title":"ISFF Based Optimal Route Selection and QoS Enhancement in VANETs","authors":"S. S, J. S. Raj","doi":"10.1109/ICSCDS53736.2022.9760786","DOIUrl":"https://doi.org/10.1109/ICSCDS53736.2022.9760786","url":null,"abstract":"With vehicles becoming the primary mode of transportation in almost all parts of the world, it has now become increasingly essential to develop advanced realtime applications that provide users with safety and entertainment regardless of their geographical location by leveraging vehicular communication. The basic communication network structure for building an efficient communication among vehicles has been formed by Vehicular Ad-hoc Networks (VANET). As a subset of Mobile Ad-hoc Networks (MANETs), the recent innovations in Vehicular Ad-hoc Networks have revolutionized the Intelligent Transportation System (ITS) paradigm. On the other hand, due to high mobility, VANET lacks the ability to develop a stable topology, which in turn results in frequent network interruptions. Amongst all the existing challenges, this paper focuses on enhancing the Quality of Service [QoS] of the VANET architectures with an optimal route selection approach - ISFF [Intelligent Swarm based Firefly Fly]. When compared to other traditional approaches, the proposed approach will help the vehicles to obtain a decision on optimal routing path. The proposed approach was simulated based on Packet Delivery Ratio [PDR] and End-to-End Delay parameters and achieved an average PDR of 62.6% and End-to-End Delay of 171.4 sec, which is comparatively higher than the existing method.","PeriodicalId":433549,"journal":{"name":"2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131876519","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

Research on Computer Network Security Framework Based on Concurrent Data Detection and Security Modelling 基于并发数据检测和安全建模的计算机网络安全框架研究

2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) Pub Date : 2022-04-07 DOI: 10.1109/ICSCDS53736.2022.9760776

Shipu Jin

引用次数: 0