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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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Accuracy Prediction for Detecting Brain Tumour from MRI Images using ResNet50

Accuracy Prediction for Detecting Brain Tumour from MRI Imag...

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international conference on Innovative Mechanisms for Industry Applications (ICIMIA)

作者： Vidyullatha Sukhavasi Shanmuga Sundari M Neha Gangisetty Naga Shushma Maharaj Computer Science and Engineering BVRIT HYDERABAD College of Engineering for Women Hyderabad Telangana

A critical step in medical care is the utilization of MRI imaging to detect brain tumors. The magnetic resonance imaging (MRI) method creates high-resolution images of the brain, making it the perfect medium for finding brain tumors. Planning a treatment strategy and diagnosing cancer can be assisted by the tumor identification and brain MRI scan segmentation. Deep learning has shown promise in several applications for image analysis, including medical image analysis. This study suggests using a pre-trained ResNet50 model in this study to find brain tumors. A deep convolutional neural network architecture called ResNet50 has demonstrated state-of-the-art performance in a variety of computer vision tasks. Researchers optimize the ResNet50 model to train it for binary classification of brain tumor vs. healthy brain images using a set of MRI brain scans. The MRI images are pre-processed by being resized to a predetermined size and having the pixel intensities normalized. The pre-trained ResNet50 model’s efficiency on the testing set is assessed using the training set amendments. This work demonstrates the usefulness of using pre-trained deep learning algorithms, like ResNet50, for brain tumor diagnosis and shows that radiologists can accurately identify and diagnose brain tumors with the use of such models.

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Role of Machine Learning in Credit Card Fraud Detection 3

Role of Machine Learning in Credit Card Fraud Detection

引用

3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Ghai, Vivek Kang, Sandeep Singh Chandigarh University Department of Computer Science Engineering Punjab India

ISBN: (纸本)9781665438117

Fraud is the occurrence of any activity done using misleading, deceptive, or illegal ways which is done by someone to defraud you of your money (or capital), or otherwise jeopardizes financial well-being of you or your company. Online fraud is defined as fraud done through the use of the internet. Identity theft or outright money fraud are both examples of online fraud. Fraud detection means a collection of activities to avoid the collecting of money/property by misleading pretensions. A number of sectors are today using fraud detection which includes ecommerce vendors and banking agencies. Due to rapid advancements within the digital commerce generation, the mode of payment has moved from cash to digital settlements such as debit/credit card, online wallet payment, and online banking, the market value of fraud detection and prevention is rising year over year. As a result, financial fraud is increasing at a rapid rate for personal gain. Banking/financial firms are developing fraud detection mechanisms to protect consumers from fraudulent transactions in response to this scenario. This paper explores different types of frauds, the limitations of existing detecting systems and the advantages of using machine learning for fraud detection. © 2021 IEEE.

关键词： Neural networks

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S2-Flow: Joint Semantic and Style Editing of Facial Images 33

S2-Flow: Joint Semantic and Style Editing of Facial Images

引用

33rd British Machine vision conference proceedings, BMVC 2022

作者： Singh, Krishnakant Schaub-Meyer, Simone Roth, Stefan Department of Computer Science TU Darmstadt Germany hessian.AI

The high-quality images yielded by generative adversarial networks (GANs) have motivated investigations into their application for image editing. However, GANs are often limited in the control they provide for performing specific edits. One of the principal challenges is the entangled latent space of GANs, which is not directly suitable for performing independent and detailed edits. Recent editing methods allow for either controlled style edits or controlled semantic edits. In addition, methods that use semantic masks to edit images have difficulty preserving the identity and are unable to perform controlled style edits. We propose a method to disentangle a GAN's latent space into semantic and style spaces, enabling controlled semantic and style edits for face images independently within the same framework. To achieve this, we design an encoder-decoder based network architecture (S2-Flow), which incorporates two proposed inductive biases. We show the suitability of S2-Flow quantitatively and qualitatively by performing various semantic and style edits. Code and data are available at https://***/visinf/s2-flow. © 2022. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Semantics

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Toward Improving Mobile Health Services in the Kingdom of Saudi Arabia Based on the Saudi 2030 vision 3

Toward Improving Mobile Health Services in the Kingdom of Sa...

引用

3rd international conference on Electrical, control and Instrumentation Engineering (ICECIE)

作者： Alsaleh, Saad Minist Hlth Res Dept Hail Hlth Cluster Hail Saudi Arabia

ISBN: (纸本)9781665449663

Mobile health (mHealth) has a vital role to play as it can improve communication and enhance the health care processes integration. The Saudi Ministry of Health (SMOH)has announced its initiatives to improve health services in the Kingdom of Saudi Arabia (KSA), and one of these initiatives is improving electronic health services. The aim of this research is to identify the most important mHealth services in the SMOH mobile applications. To achieve this aim, the study will admit a quantitative research method and the data will be collected through a questionnaire which will be distributed to patients in selected hospitals, in the (KSA. Recently, the SMOH has developed five mHelath applications in order to provide its mobile health services, however, there are several services which are not offered in these applications including appointment reservation, open and update electronic medical record, patient referee, physician directory, request medical reports and health risk assessments. The study will figure out whether these services are necessary and important for patients in the KSA. As a research implication, the research findings will expand an area of mHealth services in the KSA, which is still empirically not adequately explored. Additionally, the research results might provide valuable insights into the health professional and administrations in other countries.

关键词： Information technology mobile Health ministry of health smartphones electronic Health services

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An Integration Of Wireless Communications And Artificial Intelligence For Autonomous Vehicles

An Integration Of Wireless Communications And Artificial Int...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Kadambari Raghuram Ibrahim Altarawni Vijayalakshmi K Ajay Kumar Abhijeetsinh Jadeja Pankaj Chanda Department of Computer Science and Engineering University College of Engineering Kakinada(Autonomous) JNTUK Kakinada Andhra Pradesh Applied Computing and Artificial Intelligent Department Aqaba University of Technology Aqaba SRMIST Ramapuram Campus IT Academics iNurture Education Solution Pvt. Ltd Delhi Faculty Of Computer Science Shri C.J. Patel College Of Computer Studies Sankalchand Patel University Dept of Information Technology Guru Ghasi Das Viswavidyalaya Bilaspur Chattisgarh

The pinnacle of transportation is the development of autonomous driving, which, with the help of CAVs and related traffic management systems, can eventually lead to congestion- and accident-free driving. This vision has as of late prodded extraordinary examination interest in fields including IoV, LTE-V2X, and 5G. In any case, the huge volume of traffic information that CAVs produce makes issues for both the current organizations and the approaching 5G correspondence organizations. For outside network innovations, the VMBS fills in as both a client hub and an edge processing hub. For CAVs, it fills in as a base station and a data caching hub, melding correspondence and calculation. People offer both the VMBS-empowered handset and figuring for CAVs as well as the VMBS-helped wireless innovation for other wireless gadgets to achieve this. It is underlined and addressed that there are a number of research obstacles and open questions. Last but not least, the results of the simulation show that the planned VMBS-CCNA may significantly enhance throughput, latency, and the average amount of links.

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Synchronous Rotation Coordinates-Based Low Voltage Ride Through control Technology for Distributed VSG

Synchronous Rotation Coordinates-Based Low Voltage Ride Thro...

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Electrical Engineering and control Science (IC2ECS), international conference on

作者： Yangyang Chen Wei Han Youhao Hu Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Hong Kong SAR China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China

Traditional virtual synchronous control strategies lack the ability to perform Low Voltage Ride Through (LVRT) in the event of a fault in the distribution network. When the original power command value is high, the steady-state output current may exceed acceptable levels, and the reactive power response time may be sluggish, thereby failing to meet L VRT requirements. This paper suggests an improved L VRT control technology for VSGs using synchronous rotation coordinates. The approach suppresses instantaneous current through virtual impedance and controls output current in sequence. An improved current and power control loop is introduced, allowing the VSG to inject reactive power within a specified time and calculate active and reactive power command values for L VRT requirements. The strategy avoids the impact generated during control mode switching and meets the power grid's LVRT requirements. Simulation results validate the effectiveness of the proposed approach.

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Revolutionizing COVID-19 Management: Block chain-Enabled Prediction and Secure Storage using Deep Learning Techniques 3

Revolutionizing COVID-19 Management: Block chain-Enabled Pre...

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3rd international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Arulmozhi, B. Sheeba, J.I. Devaneyan, S. Pradeep Department of Computer Science and Engineering Puducherry Technological University Puducherry605014 India Department of Mechanical Engineering Sri Venkateshwaraa College of Engineering and Technology Puducherry605012 India

The proposed research presents a blockchain-based healthcare system that seeks to address the limitations of current data-sharing methods by providing secure and efficient data transfer, enhancing data privacy and security, enabling effective data sharing interoperability, and promoting data-driven healthcare decision-making. A blockchain platform, IPFS, and rule-based access control are among the technologies suggested for use in the proposed system. Implementing this system could result in more personalized and effective medication for patients, as well as lower healthcare costs and improved care quality. The suggested approach, known as the Homomorphic Zero-Knowledge Blockchain Algorithm (HZBA), employs a block chain technique linked with Proxy Re Encryption with Homomorphic with Zero proof knowledge. Finally, the Covid19-dataset has collected from Kaggle repository and HCDNN method has used to complete the classification. The proposed blockchain-based healthcare system has the potential to revolutionize healthcare by resolving data privacy and security concerns, increasing data accuracy, fostering more interoperability in data sharing, and enhancing data-driven healthcare decision-making. The proposed blockchain-based healthcare system provides potential answers to data sharing difficulties in the healthcare business. One potential disadvantage is the system's complexity and cost of installation. The experimental results and classification performance parameters have been thoroughly demonstrated © 2023 Elsevier B.V.. All rights reserved.

关键词： COVID-19

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Research on Individual Recognition and Prediction of Cocaine Addiction Based on Convolutional Neural Networks 23

Research on Individual Recognition and Prediction of Cocaine...

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proceedings of the 3rd international conference on Electronic Information Technology and Smart Agriculture

作者： Hongbo Xiao Jianhua Xiao Lebing Zhang Bo Tang Zhuyou Cao Tianwang Luo School of Computer and Artificial Intelligence Huaihua University China and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China School of Computer and Artificial Intelligence Huaihua University China

ISBN: (纸本)9798400716775

In response to the current difficulty in identifying and predicting cocaine addicted individuals based on brain MRI images, this paper designs a deep learning recognition and prediction model based on convolutional neural networks. 29 cocaine addicted individuals and 24 healthy controls were selected from brain MRI images. After per-forming a series of data preprocessing operations such as skull dissection and data augmentation on brain MRI images, a deep learning model based on convolutional neural networks is constructed to process the processed brain MRI images of cocaine addicted individuals and healthy controls to identify and predict cocaine addicted individuals. The experimental results show that the recognition and prediction accuracy of deep learning models based on convolutional neural networks is 89%. Compared with machine learning models such as SVM and support vector machines, it greatly improves the accuracy of model prediction and can accurately, quickly, and effectively identify and predict cocaine addicted individuals.

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Identity-Based Access control in IoT: Enhancing Security through Mutual Cryptographic Authentication and Context Awareness

Identity-Based Access Control in IoT: Enhancing Security thr...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： Priyanka More Sachin Sakhare Parikshit Mahalle Department of Computer Engineering Smt. Kashibai Navale College of Engineering Vishwakarma Institute of Information Technology Pune India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Department of Artificial Intelligence and Data Science Vishwakarma Institute of Information Technology Pune India

The proposed methodology strengthens security and privacy in IoT networks through mutual cryptographic authentication, employing Elliptic Curve Cryptography, Diffe Hellman for key exchange, and encryption methods for robust identity verification. Context awareness, considering factors like device type, communication type, successful transfers, and device behaviour, enhances access control decisions dynamically. This approach bolsters network security, defending against unauthorized access and potential threats. Identity-based access control streamlines access rights management, dynamically setting permissions for scalable network expansion. Combining cryptographic authentication and context sensitivity, this methodology emerges as a potent tool for securing IoT networks, ensuring data integrity, and preserving user privacy. Its versatility makes it applicable across diverse loT scenarios, offering a flexible and scalable access control solution. Overall, devices get authenticated with each other through identity based on clusters formed by context parameters and access rights are set to the cluster head. The cluster head is dynamically updated from time to time considering the context parameters.

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LFPS-HSDN: Link Failure Protection Scheme in Hybrid SDNs 3rd

LFPS-HSDN: Link Failure Protection Scheme in Hybrid SDNs

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3rd international conference on Advanced Intelligent Technologies, ICAIT 2022

作者： Li, Jiahui Qi, Xiaogang Zhang, Haoran Liu, Lifang School of Mathematics and Statistics Xidian University Xi’an710071 China School of Computer Science and Technology Xidian University Xi’an710071 China

ISBN: (纸本)9789819952021

Software-Defined Networks (SDNs) decouple the control plane from the data plane of forwarding devices, which can significantly improve network functions, including failure protection. In the current Internet architecture, legacy networks are gradually migrated to pure SDNs to provide flexible services, which form the hybrid SDNs. Then how to select the fewest legacy devices to upgrade to SDN switches for protecting all failed links and how to select appropriate protection paths have become the urgent problems to be tackled. In this paper, we consider the failure protection difficulty of links and the protection capability of nodes jointly, and propose the FP-SCS approach for SDN Candidate Selection (SCS) to deploy the fewest SDN switches. Based on these SDN switches, we further propose the FP-PPS algorithm for Protection Path Selection (PPS), which can flexibly select the most appropriate protection paths according to the respective importance of the interactive path parameters. The simulation results show that our proposed approaches have excellent performance compared with the state-of-the-art approaches. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hybrid SDNs Link failure protection Protection path selection SDN candidate selection Tunneling mechanism

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