2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)最新文献_第2页

Machine Learning based Prediction of Liver Disease 基于机器学习的肝病预测

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176501

Megha Bhushan, R. Krishna, Manimit Haldar, Priyanka Garg, Shreya Umrao, Tanya Rajpoot

引用次数: 0

Emotion Recognition based on fusion of multimodal physiological signals using LSTM and GRU 基于LSTM和GRU的多模态生理信号融合的情绪识别

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176510

N. Priyadarshini, J. Aravinth

{"title":"Emotion Recognition based on fusion of multimodal physiological signals using LSTM and GRU","authors":"N. Priyadarshini, J. Aravinth","doi":"10.1109/ICSCCC58608.2023.10176510","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176510","url":null,"abstract":"Emotion recognition has become an important research topic to solve the practical problems faced by humans. The traditional method of Emotion recognition using facial expressions entails social issues such as privacy threats and reliability. The state of the person's real emotion can be reflected through physiological signals which are considered to be time series data. Emotion recognition using Multi-modal physiological signals gives better discriminative information when compared to information provided by the unimodal physiological signal. In this method, various physiological signals such as ECG, EEG, Respiration, and Temperature are segmented, fused and classified using Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM). A multimodal fusion network is designed to fuse the features of four physiological signals. These features are classified into three classes namely sad, neutral and happy. The model designed is evaluated using three emotion datasets such as SEED, DREAMER and WESAD datasets respectively. From the results obtained it was observed that the proposed method achieves an average accuracy of 74% for multi-modal fusion using LSTM and 73% using GRU while 1DCNN acquired an accuracy of 61% for multi-model fusion.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130714225","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

Advances in Diabetic Retinopathy Classification using Deep Learning: The Last 5 Years Review 深度学习在糖尿病视网膜病变分类中的进展:近5年综述

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176375

Surinder Kumar, Rajneesh Rani

{"title":"Advances in Diabetic Retinopathy Classification using Deep Learning: The Last 5 Years Review","authors":"Surinder Kumar, Rajneesh Rani","doi":"10.1109/ICSCCC58608.2023.10176375","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176375","url":null,"abstract":"Diabetic retinopathy (DR) is an eye disorder that mostly affects diabetes patients and is a primary cause of vision loss all over the world. One of the key concerns that makes DR a critical condition is that it is irreversible. This means that if individuals affected by this condition do not receive appropriate treatment during the early stages, they will permanently lose their vision. Since DR is so difficult to recognize in its early stages, early diagnosis is also essential to its effective treatment. High blood sugar levels may harm the blood vessels in the retina, causing leakage, blockages, or the development of new blood vessels, all of which can cause partial vision loss or complete blindness. Several machine learning (ML) methods have been developed to recognize and categorize the condition in retinal pictures, which is DR, in order to diagnose the disease. This analysis examines recent studies that explore the use of deep learning (DL) methods. Furthermore, we go through some of the publicly available DR datasets and the metrics used to assess how well a deep learning model performs in diagnosing DR. It also highlights key conclusions and suggests areas for future research.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131193285","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

Copy-Move Forgery Localization Using DCT With LoG Filter 带日志过滤器的DCT复制-移动伪造定位

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176525

Yogitha, Rachana P, B. S, M. Reddy, R. Reddy

引用次数: 0

Estimating the Effectiveness of CNN and Fuzzy Logic for Signature Verification 估计CNN和模糊逻辑在签名验证中的有效性

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176476

Ishu Priya, N. Chaurasia

{"title":"Estimating the Effectiveness of CNN and Fuzzy Logic for Signature Verification","authors":"Ishu Priya, N. Chaurasia","doi":"10.1109/ICSCCC58608.2023.10176476","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176476","url":null,"abstract":"Each individual has a distinctive signature which is primarily used for personal authentication as well as the confirmation of significant papers or formal processes. A Signature, a form of bio-metric, is a method of authenticating the identity of an individual, thus, helping manage security. This reduces the possibility of forgery during the authentication process, and aids in avoiding any discrepancies during the signing process. But for a huge number of files, offline signature-based detection is ineffective and sluggish. Herein comes the need for automated signature verification systems. These systems aim at verifying whether a given signature image is real or fake. This paper provides a comprehensive survey of literature on various techniques used for handwriting verification including signatures. The respective findings of various methods have been discussed, highlighting the latest trends of research and their potential applications. The paper aims to present state-of-the-art methods for future development thus, serving as a helpful means for researchers carrying out study in signature verification and related topics.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"139 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128901052","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

Energy Efficient Routing Methods in Wireless Body Area Networks: A Brief Study 无线体域网络中节能路由方法的研究

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176794

Surender Singh, N. Bilandi

{"title":"Energy Efficient Routing Methods in Wireless Body Area Networks: A Brief Study","authors":"Surender Singh, N. Bilandi","doi":"10.1109/ICSCCC58608.2023.10176794","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176794","url":null,"abstract":"In these days, the concept of WBAN is widely used that is also known as Wireless Body Area Network. This kind was created once wireless sensor networks reached a particular level of development and maturity. This was probably caused by the significant advancement in wireless comfort scientific knowledge and little electronic component parts. Undoubtedly, this type of research is receiving a lot of attention these days because of its potential applications in the real world, particularly in the field of healthcare. Today, a simple sensor can be attached to a person's body to record various mental factors. This sensor can then transmit the information it collects to another device, which can then capture more significant behaviours. As WBANs typically rely on battery-powered sensors, optimizing energy consumption is essential to ensure the longevity of the sensors' battery life and the overall efficiency of the network. In order to increase energy efficiency and lower the power consumption of the sensors themselves, we examine the most efficient routing protocols utilized in WBAN in this work.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122037796","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

Image Classification of Ischemic Stroke Blood Clot Origin using Stacked EfficientNet-B0, VGG19 and ResNet-152 基于堆叠高效网- b0、VGG19和ResNet-152的缺血性卒中血凝块来源图像分类

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176805

Masabathula V S Raghavendra Rao, Surya Puligundla, Nikhil Sai Ekkala, Srilatha Chebrolu

{"title":"Image Classification of Ischemic Stroke Blood Clot Origin using Stacked EfficientNet-B0, VGG19 and ResNet-152","authors":"Masabathula V S Raghavendra Rao, Surya Puligundla, Nikhil Sai Ekkala, Srilatha Chebrolu","doi":"10.1109/ICSCCC58608.2023.10176805","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176805","url":null,"abstract":"Stroke continues to be the second-leading cause of mortality globally. Over 700,000 Americans suffer from an ischemic stroke every year as a result of a blood clot clogging a brain artery. The chances of the patient surviving a second stroke where recurrent strokes account for 23% of all incidents, are decreased. The motivation of this work is to help physicians better understand the causes of blood clots in fatal strokes, making it simpler for doctors to recommend the most effective post-stroke therapeutic management and lowering the risk of a second stroke. Whole slide digital pathology images capture the blood clot of the patient who has suffered from ischemic stroke. The objective of this work is to classify the blood clot origin in the case of ischemic stroke. Its a binary classification problem where the classes are Cardioembolism and Large artery atherosclerosis. Deep learning models can be applied to classify the stroke origin efficiently. This work proposes a stacked deep learning model with VGG19, ResNet-152, EfficientNet-B0 to classify the stroke origin. Experiments have been conducted on Mayo Clinic - Strip AI dataset from Kaggle. Comparisons have been made with these individual models and also combinations of these models and found that the proposed model is achieving lower loss value.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129703830","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

Tagging of Quarks to Particle Shower Imagery vis-à-vis Intelligent Learning 粒子雨图像中夸克的标记与-à-vis智能学习

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176833

Anurag Dutta, J. Harshith, Pijush Kanti Kumar, Yash Soni, Liton Chandra Voumik, A. Ramamoorthy

引用次数: 1

Hand Gesture Based Sign Language Recognition Using Deep Learning 基于手势的深度学习手语识别

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176912

Roli Kushwaha, Gurjit Kaur, Manjeet Kumar

引用次数: 0

Simulation of Quantum filter for estimating the spin of an electron 估计电子自旋的量子滤波器的模拟

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176884

Naman Garg, Ankur Kumar, H. Parthasarathy

引用次数: 0