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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

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Detection of Tumor-Infiltrating Lymphocytes in the Images of Immunohistochemistry using Deep Learning Techniques 7

Detection of Tumor-Infiltrating Lymphocytes in the Images of...

引用

7th international conference on Image information processing, ICIIP 2023

作者： Priya, S.Baghavathi Karuparthi, Manojna Madeswaran, TamilSelvi Computer Science And Engineering Amrita Vishwa Vidyapeetham School of Computing Chennai India University of Technology And Applied Sciences Information Technology Nizwa Oman

ISBN: (纸本)9798350371406

Deep learning is playing a pivotal role in revolutionizing the field of medicine, particularly in its ability to enhance the interpretation of histopathological images and unravel the intricate relationship between the immune system and cancer. this technology has the potential to offer a comprehensive understanding of immune cell behavior within cancer, ultimately leading to more effective diagnostic and therapeutic strategies and, in turn, improving patient outcomes. this survey is dedicated to exploring the intricate dynamics of lymphocytes in balancing pro- and anti-inflammatory activities, underscoring the critical role of tumor-infiltrating lymphocytes (TILs) as essential cancer biomarkers. With the limitations of traditional methods such as immunohistochemistry and manual cell counting in mind, the medical community is increasingly turning to machine learning. the ultimate objective is achieving precise lymphocyte detection and spatial analysis through whole-slide imaging, promising substantial advancements across various medical domains, with a primary focus on enhancing patient quality of life and healthcare precision. Notably, the use of automated methods, particularly deep learning, is being explored to address inter-individual variability in the assessment of crucial prognostic factors like Ki-67 and TILs. the introduction of the LYON19 dataset and PathoNet addresses the demand for publicly available benchmarks, with PathoNet exhibiting superior performance to date, particularly in terms of the harmonic mean measure, thus contributing significantly to medical progress. © 2023 IEEE.

关键词： Tumors

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Defending the Digital Frontier: URL-Based Phishing Detection Extension 7th

Defending the Digital Frontier: URL-Based Phishing Detection...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Vamsi, P. Muthaiah, U. Roshan Vardhan, C.H. Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9783031699856

the internet’s rapid expansion has led to an increase in cyberattacks and phishing schemes that rely on uniform resource location (URL) links. In today’s digital landscape, it’s vital to identify these harmful links for safety. Traditional methods struggle to adapt to new website URLs, so machine learning is being used to detect malicious URLs. Previous studies have explored various machine learning techniques for URL detection, but a recurring issue is the need to preprocess website links before analysis. To address this problem, a new neural network method has been introduced. this innovative approach enables the creation of a model capable of identifying malicious URLs without the need for repetitive feature extraction steps. this groundbreaking technique has shown impressive results in detecting dangerous web addresses, operating swiftly and accurately with a detection rate of 99.61%. this represents a significant advancement in the field of cybersecurity, offering an effective solution to the ever-evolving threat landscape posed by malicious URLs on the internet. © IFIP international Federation for information processing 2024.

关键词： Phishing

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An optimized Hybrid Gauss-Seidel smoother In AMG solver of Hypre on Sunway Many-core Architecture 23

An optimized Hybrid Gauss-Seidel smoother In AMG solver of H...

引用

7th international conference on High Performance Compilation, Computing and Communications, HP3C 2023

作者： Tian, Min Liu, Yue Du, Wei Xiao, Lei Liu, Qi Wang, Xinhua Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9781450399883

the multigrid algorithm is a commonly utilized iterative technique for resolving vast and sparse matrix equations in numerical computation. Hypre is an open-source library of high-performance preconditioners and solvers, incorporates multigrid methods and enables efficient resolution of large, sparse linear systems on parallel computers. We employed a master-slave acceleration model for Algebraic Multigrid method on sunway architecture. Address mapping and intervention strategies for CPE are adopted. Numerical experiments that we proposed optimized algorithm result in speedup of nearly nine times compared to the original version. this showcases the model's effectiveness in accelerating the resolution of large, sparse linear systems. © 2023 ACM.

关键词： Parallel processing systems

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RVTN: Recommender system for vehicle routing in transportation network 7

RVTN: Recommender system for vehicle routing in transportati...

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7th international conference on Parallel, Distributed and Grid Computing, PDGC 2022

作者： Tandon, Righa Verma, Ajay Gupta, P.K. Chitkara University Institute of Engineering and Technology Chitkara University Department of Computer Science and Engineering Punjab India Jaypee University of Information Technology Department of Computer Science and Engineering Solan India

ISBN: (纸本)9781665454018

the recommender system predicts the future paths based on the vehicle interactions in a vehicular environment. As the data is ubiquitous, we have a number of options available to make a selection for finding the path in the vehicular network. this is the scenario where the recommender system plays its role by narrowing the available options and make the selection process easy and effective. In this paper, we have proposed a sequential recommender system that considers the vehicle's interactions along with the paths in sequential order and map the sequences dynamically in which the weight-age is given to current preferences and recent choices as explored by the vehicle of the network. A detailed comparison of the proposed sequential recommender system with the commonly used matrix factorization model has also provided. the proposed recommender system is based on sequential dependencies and responds equally well to the vehicle routing problem. the obtained results using vehicle routing dataset reveals that the proposed recommender system is much faster with higher Mean reciprocal rank (MRR) value. © 2022 IEEE.

关键词： Vehicles

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Incorporating Social Relationships for Multi-modality Person Re-identification 7

Incorporating Social Relationships for Multi-modality Person...

引用

7th international conference on computer and Communication Systems, ICCCS 2022

作者： Zhu, Chuanhu Huang, Likun Wang, Yue Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

Person re-identification (ReID) which aims to retrieve particular persons across non-overlapped cameras is very important to intelligent security system. Most previous methods of re-id focused on learning individual appearance feature embedding, but it is hard for the models to deal with many difficult situations such as occlusions. there are also some works those have attempted to integrate multi-modal cues, e.g. clothes and social relations. While showing improvements, they still have some limitations, such as designing too many objective functions to guide the model and relying on simple heuristics to combine multi-modal cues. In this paper, we propose a new framework to solve the above problems. Specifically, our model consists of three branches to extract and fuse information under three modalities respectively. the model can effectively utilize the information of person appearances, background scenes and social relationships in images to infer the identity of the person. the experimental results show that our method outperforms the state-of-the-art on the public datasets. © 2022 IEEE.

关键词： Social aspects

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VSMAS2HN: Verifiably Secure Mutual Authentication Scheme for Smart Healthcare Network 1

引用

Proceedings of the 7th international conference on Advances in Computing and Data Sciences, ICACDS 2023

作者： Batra, Shivangi Narwal, Bhawna Mohapatra, Amar Kumar Delhi India

ISBN: (数字)9783031379406

ISBN: (纸本)9783031379390

Digitization has reformed and revamped the healthcare industry and ameliorated patient-clinician interaction. technology has coherently modified conventional medical workflow and successfully decentralized and stabilized communication between caregivers and patients, making medical services more affordable and accessible to patients. the Internet of Medical things (IoMT) has efficaciously unified the healthcare ecosystem and made remote patient monitoring more adaptable and reachable. Due to the accessible and economical attributes, incorporating cloud technology has been effective for smart healthcare infrastructure. Nonetheless, the security of sensitive patient data from cyber threats is the key concern for cyber experts. Securing the IoMT network is a pressing priority thereby this paper proposes a VSMAS2HN: A Verifiably Secure Mutual Authentication Scheme for Smart Healthcare Networks. the proposed VSMAS2HN has been tested "SAFE" over AVISPA and BAN Logic has also been presented to support the secure nature of the session key of the suggested scheme. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hospital data processing

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A Driver Distraction Detection Method Based on Convolutional Neural Network 7

A Driver Distraction Detection Method Based on Convolutional...

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7th international conference on computer and Communication Systems, ICCCS 2022

作者： Wei, Chuheng Liu, Chuanshi Chi, Shaocui The University of Warwick Warwick Manufacturing Group Coventry United Kingdom Jilin University School of Mechanical and Aerospace Engineering Changchun China Communication University of China School of Information and Communication Engineering Beijing China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

the growth of the economy and technology is increasing the popularity of automotive, but it also increases the number of traffic accidents. the driver's factor is a major cause of traffic accidents and ensuring the driver's concentration while driving is an essential research topic along with the development of autonomous cars. Recent developments in artificial intelligence and advanced hardware systems have made convolutional neural networks increasingly useful in computer vision. the purpose of this article is to explore the use of ResNet-50 neural networks in detecting driver distractions. In this article, the performance of ResNet-50 neural network is studied and analyzed and the possibility of its use for distraction detection is explored. In addition, it is found that this neural network is more capable of classifying whether a driver is distracted than of classifying their specific distracted behavior. © 2022 IEEE.

关键词： Convolution

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dScout : Unmanned Ground Vehicle for Automatic Disease Detection and Pesticide Atomizer 7

dScout : Unmanned Ground Vehicle for Automatic Disease Detec...

引用

7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Reddy, Buchammagari Avinash Krishna, Ghanta Sai Saraswathi, Kaniganti Priyanka Sadhvika, Indala Udutalapally, Venkanna Das, Debanjan Iiit Naya Raipur India

ISBN: (纸本)9781665421683

Agriculture Cyber-Physical System (A-CPS) is intensively gaining significance in achieving precision agriculture. Plant diseases are the major problem in the agricultural sector, which affects crop production and, in return, affects the economic profit of India as most people are dependent on agriculture. In conventional agriculture, manual monitoring of crops is laborious, slow, and error-prone process to be implemented. the economic and production loss due to plant diseases can be tackled with continuous plant monitoring. Contributing towards precision agriculture, the proposed system (dScout) is able to automate the real-time problem of leaf disease detection with deep computer vision and the Internet of things. this paper deals with the automation of image acquisition using Raspberry pi and smart line tracking robot, identification of leaves with YoloV3 CNN architecture, the spread of infection with image processing, and disease detection with InceptionV3, and automatic pesticide sprayer. the trained InceptionV3 model has achieved 90.51% accuracy and can differentiate nine tomato leaf diseases. the automatic pesticide sprayer is integrated with Raspberry pi, which predicts the diseases in images with the SVM model. the results are synchronized to the cloud and mobile interface. dScout provides a high-performance working solution for automatic crop disease detection and detailed disease prevention suggestions under the real agricultural environment. © 2022 IEEE.

关键词： computer vision

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Design and Implementation of a System for Vehicle Accident Reporting and Tracking 7

Design and Implementation of a System for Vehicle Accident R...

引用

7th international conference on Communication and Electronics Systems, ICCES 2022

作者： Gowda, V. Dankan Sharma, Avinash Naik, Anil S. Meena, Radhey Shyam Kudari, Jayashree M. Purushotham, S. BMSITandM Department of Electronics and Communication Engineering Karnataka Bangalore India Maharishi Markandeshwar Engineering College Department of Computer Science Engineering Haryana India National Institute of Technology Karnataka Surathkal India Indian Institute of Technology Department of Industrial and Management Engineering Uttar Pradesh Kanpur India Jain Deemed to Be University Department of Computer Science and Information Technology Karnataka Bangalore India Sona College of Technology Department of Electrical and Electronics Engineering Tamilnadu Salem India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Population growth and per capita income have contributed to increasing vehicle ownership and presence on roads worldwide. Increasing traffic on roads is one of the prime causes of road accidents. A large proportion of people die prematurely in road accidents. It is almost impossible to predict before the accident happens. Also, there may be some accident prevention mechanisms and early warning systems, but it is hard to avert road accidents wholly. this paper has explained in detail, the designing and implementation of a crash notifier system. © 2022 IEEE.

关键词： Roads and streets

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Chat Bot in Banking Sector Using Machine Learning and Natural Language processing 7th

Chat Bot in Banking Sector Using Machine Learning and Natura...

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7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Chokkalingam, S.P. Krishna, Pasumarti Vamsi Harshath, V. Reddy, Chavva Bala Kuswanth Sandeep, Yenumula Siva Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science Engineering Amrita School of Computing Amrita Vishwa Vidyapeetam Chennai601103 India

ISBN: (纸本)9783031699818

the demand for the effective customer services in banking industry has increased day by day and requirement of perfect solutions for the customer query also increased in these modern days. this research paper says about the design, development, various kind of chat bots present in now a days and how these chat bots are implemented and in which way it works according to customer queries. Chatbots are actually created to give accurate answers for banking inquires. the chat bot provides a user friendly interface for customers, they can ask information about their account balance, transaction history, fund transfer, loan application and other common banking tasks. the research methodology includes methods for how to access a normal chat bot in easy steps and various chatbots present now a days in banking industry and training of chatbot to understand and respond to diverse customer queries. the chat bot has advance machine learning algorithms and natural processing language to adapt for different queries and improve its performance in future and ensuring the perfect accuracy level of the answers. the system is combined with bank database so customers can see their bank details, ensuring real time access for their account information, secure transaction. Our research findings reveals that after coming of chat bot in banking sector the human customer services has been decreased and customer satisfaction has increased. After many testing of this model and according to user feedback the chat bot provides accurate solutions for their quires except in some situations. this research contains about growing field of artificial intelligence customer service solutions and potential benefits of implementing a banking chat bot to address common customer services ultimately leading to improved customer engagement and loyalty. © IFIP international Federation for information processing 2024.

关键词： Customer satisfaction

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