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检索条件"任意字段=4th International Conference on Computing and Data Science, CONF-CDS 2022"

共 1120 条记录，以下是181-190 订阅

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Hybrid Classification Approach with Textural Feature Analysis for Plant Disease Detection 4

Hybrid Classification Approach with Textural Feature Analysi...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Kumar, Ravindar Jindal, Vikas Chandigarh University Department of Computer Science Mohali India

ISBN: (纸本)9781665474368

the significant task of image processing in the domain of plant disease is of diagnosing the diseases occurred on plants because much complicated data is employed as input. Different stages are executed to detect the plant diseases using several techniques. the earlier work suggests SVM technique for diagnosing plant infections. this work projects a voting mechanism to improve various parameters like accuracy, precision and recall in comparison with the traditional methods. the projected mechanism was simulated using MATLAB. An analysis is conducted on the results with regard to some metrics. the outcomes exhibited that the projected mechanism is more effective as compared to other method. the proposed model achieves accuracy of 96 percent which approx. 3 percent higher as compared to existing SVM classifier. © 2022 IEEE.

关键词： Diagnosis

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Human Violence Detection Using LHOGF Algorithm and Deep Learning Model 4

Human Violence Detection Using LHOGF Algorithm and Deep Lear...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Chauhan, Akash Gupta, Ruchika Chandigarh University Computer Science and Engineering India

ISBN: (纸本)9781665474368

A minor action of human is performed with some purpose. Understanding the behavior and the way to interact of human with environment in automatic way has attained a lot of attention in research field over past few years due to its potential in diverse domains. Several applications such as intelligent video surveillance and for monitoring the environmental home, for storing and retrieving the video etc. are related to the domain of recognizing the human activity. the human violence is detected in several stages in which the data is pre-processed, features are extracted, and the data is classified. this research introduces a deep learning algorithm for predicting the human violence. Python is executed to simulate the introduced algorithm and diverse metrics such as precision, and recall are considered to analyze the outcomes. the proposed model shows significant high performance as compared to existing model. © 2022 IEEE.

关键词： Python

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Applications of Deep Learning for Disease Management 4

Applications of Deep Learning for Disease Management

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Yadav, Rashmi Bhat, Aruna Delhi Technological University Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9781665474368

the current scenario indicates that every person suffers from a disease. thus, in the current framework, disease management is a must. It includes disease detection, diagnosis, prediction, and analysis. Deep learning (DL) plays a dynamic role in the healthcare area. the Healthcare sector uses various DL technologies such as Convolutional Neural Network (CNN), Stacked Encoders (SAE), Recurrent Neural Network (RNN), Deep Neural Network (DNN), etc. to find accuracy in the data. Various technologies like X-Ray, Computed Tomography (CT) scans, and Magnetic Resonance Imaging (MRI) also uses DL. this study presents a detailed work of recent research on DL in healthcare. © 2022 IEEE.

关键词： Deep neural networks

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Analysis of Bio-Inspired Optimization Algorithms in Feature Selection for Facial Expressions Recognition 4

Analysis of Bio-Inspired Optimization Algorithms in Feature ...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Jagadeesh, M. Baranidharan, B. Srm Institute of Science and Technology Dept. of Computing Technologies Tamilnadu Chennai India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

there are several popular methods for extracting facial expression features but finding the most significant features of a particular data sample and weeding out the rest that doesn't help us make better decisions has always been difficult. the Feature selection algorithm aims to solve this issue by removing irrelevant and repeated features. Feature selection involves including vital features or removing unimportant ones without changing them. Statistics methods traditionally used are ineffective as they increase the number of data samples and features to each sample. Feature selection techniques are used for several reasons [1]: (1) It eliminates unnecessary features from the model and reduces its complexity, (2) Accelerates the training process of ML algorithms, (3) Dimensional reduction reduces over-fitting, and (4) Builds a more accurate model. Recent advancements in swarm intelligence (SI) technologies have helped overcome these challenges. this research study compares various feature selection methods and then analyzes the meta-heuristic approaches based on swarm intelligence to solve the optimization challenges. © 2022 IEEE.

关键词： Feature Selection

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Sentiment Analysis on Amazon Alexa Reviews Using NLP & Classification 4

Sentiment Analysis on Amazon Alexa Reviews Using NLP & Class...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Kumar, Sanjay Kanshal, Sahil Sharma, Vishnu Talwar, Rajneesh Chandigarh Group of Colleges Jhanjeri Department of Computer Science Engineering Mohali India Jims Department of Information Technology Delhi India Galgotia's College of Engineering and Technology Department of Computer Science Engineering Greater Noida India Chandigarh Group of Colleges Jhanjeri Department of Electronic & Communication Engineering Mohali India

ISBN: (纸本)9781665474368

many firms and manufacturers, knowledge on public opinion is critical. they frequently want to know what consumers and the general public think of their products and services in real time. However, personally reading every post on the website and extracting important viewpoint information is not feasible. the frequency of data is very high to do it manually. Sentiment analysis enables for efficient and cost-effective data processing on a wide scale. We investigated the application of sentiment analysis in business to better understand its strengths and limits in order to learn more about it. Using Python and Machine Learning Algorithms, this project created a representation to forecast the response of a remark given the observation declaration using a dataset of Amazon Alexa reviews. © 2022 IEEE.

关键词： Cost effectiveness

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License Number Plate Recognition(LNPR) 4

License Number Plate Recognition(LNPR)

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Garg, Khushi Gautam, Kapil Singh, Karamveer Gaur, Madhvi Abes Engineering College Ghaziabad Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9781665474368

License number plate recognition is a technology which is used to detect the number of vehicles;it can be achieved by the OCR (optical character recognition) and OpenCV which is a computer vision technology. Most of the time the accuracy depends on hardware which is used to collect the data and the environment also like whether, Lighting. LNPR can be used in for traffic system where police can easily identify the vehicle number with the help of LNPR and it can be used in toll-tax areas where road authority can used it to get the tax from the public. It can also be used in the parking areas to get the data which vehicle is present at which time.. ANPR is a fascinating subject for academics because of its unreliability, tough surroundings, and other complications. © 2022 IEEE.

关键词： Optical character recognition

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UWSN Survey: Challenges and Application issues 4

UWSN Survey: Challenges and Application issues

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Astya, Rani Jha, C.K. Banasthali Vidyapeeth Rajasthan Sharda University Department of Computer Science India Banasthali Vidyapeeth Department of Computer Science Rajasthan India

ISBN: (纸本)9781665474368

In the last few years, research has increased enormously in the field of the underwater domain. It is mainly due to the vast unexplored area of earth covered by river, sea water and needs exploration in multiple dimensions, including offshore and underwater networking environments. Compared to the terrestrial domain, there are many challenges due to seawater's inherent properties, including viscosity, pressure, turbidity, etc. these all require effective solutions for different useful applications like the study of marine life, sea resources exploration, naval surveillance, etc. in terms of effective communication and routing of data from one end to another, deployment and mobility of nodes, etc. this paper has presented a literature review, comparative study, and feasible tools which can be useful in proving solutions for underwater sensor networking issues. © 2022 IEEE.

关键词： Viscosity

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Security Intensification using Blockchain coupled with Internet of things: Proposal, Challenges and Anatomization 4

Security Intensification using Blockchain coupled with Inter...

引用

4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Anand, M. Vivek Sabharwal, Munish Vijayalakshmi, S. Galgotias University School of Computing Science and Engineering Greater Noida201308 India Christ University Dept of Data Science 412112 India

ISBN: (纸本)9781665474368

Internet of things is an important part of our day-to-day life where all things are connected in the network with the internet. the number of devices linked to the network grows steadily each day in recent years. the innovation in the manufacturing industry also the reason for the production of different devices that uses various technologies to make a possible connection between the devices. Even though the Internet of things has been developing and demonstrating its potential in recent years, its security when connected to the internet is in doubt. Blockchain is a disruptive technology that provides security to their network without tampering with the data in the network. Researchers and experts have recommended using the blockchain to address security vulnerabilities in the Internet of things. In this paper, we have analyzed some of the issues which are occurring while integrating blockchain into the Internet of things. the major issues were discussed and which will be helpful to move towards the research direction to solve those problems. © 2022 IEEE.

关键词： Blockchain

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the Evaluation data Mining of the Comprehensive Practice Platform of Single-Chip Microcomputer in Vocational Colleges based on the Intelligence of Skill Competition Assessment 4

The Evaluation Data Mining of the Comprehensive Practice Pla...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Chen, Zhiyou Jiangsu Union Technical Institute Suzhou Industrial Park Branch Jiangsu Suzhou215000 China

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Based on summarizing the basics of my own training attempts in the single-chip skill competition, this paper thinks about the teaching reform of secondary vocational single-chip microcomputer courses from the perspectives of teaching content, teaching methods, and assessment methods. the current situation and development trend of the experimental teaching platform of single-chip microcomputer are investigated and studied, and its success and shortcomings are analyzed. Introduced, and other related knowledge. and use data warehouse and online analysis and processing technology to build a comprehensive evaluation system of teaching quality combining 'plane' and 'three-dimensional', and establish a multi-dimensional comprehensive evaluation online analysis mining model. © 2022 IEEE.

关键词： data mining

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SCADA Intrusion Detection System using Cost Sensitive Machine Learning and SMOTE-SVM 4

SCADA Intrusion Detection System using Cost Sensitive Machin...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Mahalakshmi, M. Ramkumar, M.P. Emil Selvan, G.S.R. Thiagarajar College of Engineering Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9781665474368

Emerging technologies throughout the world work with the baseline of Cyber Physical Systems (CPS) to provide remote accessibility. Large scale industries make use of CPS infrastructure, known as Industrial Control Systems (ICS). the ICS using the Supervisory Control And data Acquisition systems (SCADA) provides remote accessibility, which are highly prone to cyber-attacks. Here arises the need of Intrusion Detection System (IDS). Any Machine Learning (ML) based IDS heavily depends on the historical data, in that case, the class imbalance problem plays a crucial determinant factor of the IDS performance. thus, the re-search is to address the adverse effects of the class imbalance problem in ML based IDS using a hybrid approach. To do so, the SCADA dataset of the gas pipeline critical infrastructure, is used. To handle the imbalanced data problem, the Synthetic Minority Oversampling Technique with Support Vector Machine (SMOTE_SVM) is adopted as a data level solution combined with an algorithmic level solution, Cost-Sensitive Machine Learning (CSL) is adopted. Different evaluation metrics are used to evaluate the performance of the ML model with and without data balancing techniques. From the results, the hybrid approach of SMOTE-SVM with CSL is proven to be an efficient method to deal with the effects of the imbalanced dataset. the hybrid approach exhibits the following met-rics on using Logistic Regression tuned as CSL;the highest precision and recall scores with 69% and 66% respectively and a zero False Alarm Rate (FAR). © 2022 IEEE.

关键词： Support vector machines

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