2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC)最新文献_第5页

Beauty of Blockchain Technology in Healthcare Industry 区块链技术在医疗行业的美

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10084089

Parthasarathi Pattnayak, Arpeeta Mohanty, T. Das, Sanghamitra Patnaik

引用次数: 1

AO2DS: A Method of Auxiliary Operational Decision-making Based on System Dynamics Simulation AO2DS:基于系统动力学仿真的辅助作战决策方法

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10084273

Zhongyuan Ren, Xuejun Ren, Lin-jiao Ren

引用次数: 0

Performance Analysis of an ANN-based model for Breast Cancer Classification using Wisconsin Dataset 基于威斯康星州数据集的人工神经网络乳腺癌分类模型的性能分析

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10083642

Utkarsh Srivastava, Vidushi Vaidehi, T. Koirala, Palash Ghosal

引用次数: 0

Learning Techniques for Depression Detection: A Comparative Studies 抑郁检测的学习技巧:比较研究

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10083576

A. Das, Mrinal Kanti Debbarama, R. K. Barik

引用次数: 0

Power of kernel functions, its benefits, and limitations 核函数的功能、优点和局限性

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10084201

R. Indu, S. Dimri

引用次数: 0

The COVID'19 Dashboard with Implementation of Face Mask Detection and Social Distancing Detection Algorithm 实现口罩检测和社交距离检测算法的COVID'19仪表板

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10084284

M. Nair, Gadiparthy Harika Sai, P. V., H. Sriraman

{"title":"The COVID'19 Dashboard with Implementation of Face Mask Detection and Social Distancing Detection Algorithm","authors":"M. Nair, Gadiparthy Harika Sai, P. V., H. Sriraman","doi":"10.1109/ISACC56298.2023.10084284","DOIUrl":"https://doi.org/10.1109/ISACC56298.2023.10084284","url":null,"abstract":"With the outbreak of the global pandemic, India seemed to reach its peak with regard to the number of confirmed positive cases in the months of April and May. Hence, the decision was made to develop a data visualization project with one of the efficient visualization tools Tableau to help people analyze the scenario of the cases across the country. To contribute to state-wise and country-wise analysis of COVID cases in India, 2 dashboards have been developed. The first dashboard consists of the analysis of cases across the country giving a holistic and overall view of the number of deaths, positive cases, and density of cases in each state which is done through color variation. On the other hand, the second dashboard gives a detailed state-wise analysis of cases with the necessary parameters and details catering to every individual state as per the preference of the user. On merging these components, users can get an all-inclusive analysis based on different parameters on the COVID'19 cases across India at a glance. In order to prevent a further spike in cases, implementing a face mask detection system will also take place after conducting a thorough analysis of the possible machine learning algorithms. Two major object detection algorithms were taken into consideration and based on the conclusion drawn, the best algorithm – RCNN was used to implement the face mask detection system. This project is solely motivated by the current extreme situation in the world and as an attempt to provide a solution to combat the same.","PeriodicalId":211409,"journal":{"name":"2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127203276","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

The Role of Deep Learning in Diagnosis and Grading of Diabetic Retinopathy: A Review 深度学习在糖尿病视网膜病变诊断和分级中的作用综述

2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) Pub Date : 2023-02-03 DOI: 10.1109/ISACC56298.2023.10084051

Samarpit Minz, Saarthak Seth, Sarvesh Tiwari, R. Katarya

{"title":"The Role of Deep Learning in Diagnosis and Grading of Diabetic Retinopathy: A Review","authors":"Samarpit Minz, Saarthak Seth, Sarvesh Tiwari, R. Katarya","doi":"10.1109/ISACC56298.2023.10084051","DOIUrl":"https://doi.org/10.1109/ISACC56298.2023.10084051","url":null,"abstract":"In developing nations, diabetic retinopathy is a leading cause of blindness. It often has no early warning signs; however, monitoring the eyes could prevent the progression to more severe forms of sight-threatening retinopathy and macu-lopathy. The primary diagnostic method for diabetic retinopathy is analyzing fundoscopic images; however, manually examining such images can be time-consuming and unreliable because the ability to spot abnormalities varies with the physician's exper-tise. This manual effort has been lessened by computer-aided diagnosis tools that automatically detect diabetic retinopathy on retinal scans. Deep Learning techniques offer an excellent way of creating computer-aided diagnosis tools, delivering highly efficacious diabetic retinopathy detection and grading results. This review lists the current state-of-the-art Deep Learning approaches in the application of detection and grading of diabetic retinopathy, some of which include transfer learning, Convolutional Neural Networks, and object detection techniques, among others. It further identifies potential research gaps in these approaches and the future research direction to find solutions to address them.","PeriodicalId":211409,"journal":{"name":"2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129450912","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