2022 International Conference on Connected Systems & Intelligence (CSI)最新文献

Fake News Article classification using Random Forest, Passive Aggressive, and Gradient Boosting 使用随机森林、被动攻击和梯度增强的假新闻文章分类

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924131

S. T. S., P. Sreeja, Rajeev J Ram

引用次数: 0

Gesture based Real-Time Sign Language Recognition System 基于手势的实时手语识别系统

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924024

Tiya Ann Siby, Sonam Pal, Jessica Arlina, S. Nagaraju

{"title":"Gesture based Real-Time Sign Language Recognition System","authors":"Tiya Ann Siby, Sonam Pal, Jessica Arlina, S. Nagaraju","doi":"10.1109/CSI54720.2022.9924024","DOIUrl":"https://doi.org/10.1109/CSI54720.2022.9924024","url":null,"abstract":"Real-Time Sign Language Recognition (RTSLG) can help people express clearer thoughts, speak in shorter sentences, and be more expressive to use declarative language. Hand gestures provide a wealth of information that persons with disabilities can use to communicate in a fundamental way and to complement communication for others. Since the hand gesture information is based on movement sequences, accurately detecting hand gestures in real-time is difficult. Hearing-impaired persons have difficulty interacting with others, resulting in a communication gap. The only way for them to communicate their ideas and feelings is to use hand signals, which are not understood by many people. As a result, in recent days, the hand gesture detection system has gained prominence. In this paper, the proposed design is of a deep learning model using Python, TensorFlow, OpenCV and Histogram Equalization that can be accessed from the web browser. The proposed RTSLG system uses image detection, computer vision, and neural network methodologies i.e. Convolution Neural Network to recognise the characteristics of the hand in video filmed by a web camera. To enhance the details of the images, an image processing technique called Histogram Equalization is performed. The accuracy obtained by the proposed system is 87.8%. Once the gesture is recognized and text output is displayed, the proposed RTSLG system makes use of gTTS (Google Text-to-Speech) library in order to convert the displayed text to audio for assisting the communication of speech and hearing-impaired person.","PeriodicalId":221137,"journal":{"name":"2022 International Conference on Connected Systems & Intelligence (CSI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129014256","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

Neural Network Detector in Mobile Molecular Communication for Fast Varying Channels 快速变信道移动分子通信中的神经网络检测器

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924143

U. K. Agrawal, A. Shrivastava, Debanjan Das, R. Mahapatra

引用次数: 0

Vehicle Classification and Counting for Traffic Video Monitoring Using YOLO-v3 基于YOLO-v3的交通视频监控车辆分类与计数

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924018

Samprit Bose, Chavan Deep Ramesh, M. Kolekar

引用次数: 1

DARKWEB IMAGE SCRAPPER: An Open Source Intelligence Tool 暗网图像抓取器:一个开源的智能工具

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924098

Ashwini Sasi, Varun Nair, Vipin P

引用次数: 0

Stock Trading Signal Filtering Based on Bagging-RF-LR Model 基于Bagging-RF-LR模型的股票交易信号滤波

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924019

Zitong Li, T. Lin, Xia Zhao

引用次数: 0

A Secure Key Agreement Mechanism for Smart Home Networks 智能家庭网络的安全密钥协议机制

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924103

Raushan Kumar Singh, Akshay Kumar, M. Hussain

引用次数: 0

Analysis of Combinational Delay in Signed Binary Multiplier 符号二进制乘法器的组合延迟分析

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9924000

N. Behera, Monoranjan Pradhan, P. Mishro

{"title":"Analysis of Combinational Delay in Signed Binary Multiplier","authors":"N. Behera, Monoranjan Pradhan, P. Mishro","doi":"10.1109/CSI54720.2022.9924000","DOIUrl":"https://doi.org/10.1109/CSI54720.2022.9924000","url":null,"abstract":"In a Very Large Scale Integration (VLSI) Field, multipliers play a vital role. In practice, multipliers are utilizing as unsigned and signed category. An unsigned multiplier does the multiplication of two unsigned binary integers, whereas in signed multiplier the multiplication is done by every bit of binary integers. It can be expanded within its series or a suitable outcome. In the prose, most of the research has been stated that describes signed multiplication such as Booth, Baugh-Wooley, Wallace tree, Array multiplier proposed the elevated speed signed product procedures. However, there is a possibility will get the better performance of delay, power and speed in the signed multiplier. In this paper, author proposed a signed multiplier utilizing “Urdhva Tiryabhyam” (UT) algorithm. The suggested intend structure is appropriate for the conversion of signed and unsigned binary multiplication and decimal multiplication. Using of Vedic algorithm in the suggested work, the system performance is progressed and the area is minimized. The proposed structure is simulated and synthesized using ISE Xilinx 14.5 and implemented in Virtex 4 Field Programmable Gate Array devices (FPGA). The recommended work is compared among the prior architectures. From the outcomes the greatest of the author's design is taken.","PeriodicalId":221137,"journal":{"name":"2022 International Conference on Connected Systems & Intelligence (CSI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130953632","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

Residual Networks and Deep-Densely Connected Networks for the Classification of retinal OCT Images 残差网络和深度密集连接网络在视网膜OCT图像分类中的应用

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9923993

M. Mathews, S. M. Anzar

{"title":"Residual Networks and Deep-Densely Connected Networks for the Classification of retinal OCT Images","authors":"M. Mathews, S. M. Anzar","doi":"10.1109/CSI54720.2022.9923993","DOIUrl":"https://doi.org/10.1109/CSI54720.2022.9923993","url":null,"abstract":"Diabetic macular edema (DME) and drusen macular degeneration (DMD) are two se-vere vision-threatening diseases affecting the mac-ula of the eye. This study presents deep learning based classification models for retinal optical co-herence tomography (OCT) images that distinguish between healthy eyes, DME and DMD cases. The work involves the use of residual models, and deep and densely connected networks for the analysis of OCT images. This involves pre-initialisation of the model using the ImageNet dataset, followed by fine-tuning with OCT images. Both models are very powerful and suitable for real-time use in clinical practise. ResidualNets use skip connections, where the output of the previous layer is added to the layer before it. DenseNets use dense connections between the convolutional layers of the network, which allows deeper supervision between layers. This makes it easier for the model to learn the complex feature maps of the images of OCT in each layer of the network. The models are trained and evaluated using the Mendeley OCT dataset, a publicly available SD-OCT dataset for the retina. We calculate the F1 score, accuracy, precision and recall to evaluate the models. The models provide excellent performance without requiring any pre-processing steps. The promising performance of the computerised systems prove that they can serve as automatic recognition tools to assist ophthalmologists.","PeriodicalId":221137,"journal":{"name":"2022 International Conference on Connected Systems & Intelligence (CSI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121528236","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

Automated sensor test system using Raspberry Pi 自动传感器测试系统使用树莓派

2022 International Conference on Connected Systems & Intelligence (CSI) Pub Date : 2022-08-31 DOI: 10.1109/CSI54720.2022.9923977

A. Sreejithlal, M. N. Syam, T. M. Letha, K. P. M. Madhusoodanan, R. Warrier, A. Shooja

引用次数: 0