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Investigating the Benefits of machine Learning Algorithms for Text Classification 3

Investigating the Benefits of Machine Learning Algorithms fo...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Gowrishankar, J. Vinithra Banu, T. Parikshit, N. Singh, Vandana Kalra, Hitesh Sahoo, Girija Shankar Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350319125

This paper affords a research into using gadget studying algorithms for textual content category duties, with a focal point on understanding the importance of these algorithms and their ability to enhance the accuracy of textual content classification. it's miles located that, while conventional techniques, which include rule based models and hand-engineered features, can attain first-class outcomes, there are compelling motives to explore the capability of device getting to know algorithms to further improve the accuracy and performance of textual content class. The paper discusses the 3 maximum famous gadget gaining knowledge of algorithms for this project: the NaÏve Bayes classifier, help Vector machines, and synthetic Neural Networks, and presents a top level view of the latest research findings that demonstrate the prevalence of these algorithms over traditional methods. The paper additionally presents an outline of the distinctive approaches for introducing era into text type, and discusses modern-day strategies for implementing and deploying those algorithms. Finally, the paper outlines ability areas for destiny research associated with information the results of system studying algorithms for this mission, and suggests viable instructions for exploration. © 2023 IEEE.

关键词： Classification (of information)

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Hybrid Deep Learning Cloud Intrusion Detection 3

Hybrid Deep Learning Cloud Intrusion Detection

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3rd IEEE international conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Karnan, Lokanayaki Mahalakshmi, S.B. Thirunavukkarasu, V. Christ University Department of Computer Science Karnataka Bangalore560029 India Coimbatore Institute of Technology Department of Artificial Intelligence & Machine Learning Tamil Nadu Coimbatore641014 India

ISBN: (纸本)9798350361186

The scalability and flexibility that cloud computing provides, organisations can readily adapt their resources to meet demand without having to make significant upfront expenditures in hardware infrastructure. Three main types of computing services are provided to people worldwide via the Internet. Increased performance and resource access are two benefits that come with using cloud computing, but there is also an increased chance of attack. As a result of this research, intrusion detection systems that can process massive amounts of data packets, analyse them, and produce reports using knowledge and behaviour analysis were created. Convolution Neural Network Algorithm encrypts data as it's being transmitted end-to-end and is stored in the cloud, providing an extra degree of security. Data protection in the cloud is improved by intrusion detection. This study uses a model to show how data is encrypted and decrypted, of an algorithm and describes the defences against attacks. When assessing the performance of the suggested system, it's critical to consider the time and memory needed to encrypt and decrypt big text files. Additionally, the security of the cloud has been investigated and contrasted with various encoding techniques now in use. © 2024 IEEE.

关键词： Intrusion detection

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An Artificial intelligence Approach to Quantifying Exercise Form for Optimal Performance and Injury Prevention 3rd

An Artificial Intelligence Approach to Quantifying Exercise ...

引用

3rd international conference on Computing and Communication Networks, ICCCN 2023

作者： Sowmia, K.R. Jayaganeshan, T. Mohammed Abraar Khan, F. Madhesh, S. Kabilesh, S. Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Tamil Nadu Chennai India

ISBN: (纸本)9789819708918

Human body posture estimation remains one of the most challenging problems despite substantial research and improvements in the fields of artificial intelligence and computer vision. Human pose detection has several uses, including assisted living, video surveillance, biometrics, public security, and at-home health monitoring. Nowadays, teenagers between the ages of sixteen and twenty-five are encouraged to engage in rigorous training because they are interested in maintaining a specific degree of physical fitness in their bodies. If they do not maintain good form or posture, this tough training activity could lead to muscular injuries or any other small or serious problems. They should engage a personal trainer or someone who can help them follow the right methods to sustain and prevent injuries if they want to keep up with all of this. This only applies to those who perform these intense exercises in a gym or other public space;at-home exercisers would not be able to afford personal trainers and instructors. One can utilize an AI-trained model to maintain good body posture for intense workouts. The analysis and evaluation of the participants’ exercise movements will be done by the study using a combination of motion sensors, cameras, and machine learning algorithms. The AI-powered system will examine each participant's form, offer real-time feedback, and correct mistakes made while training with various workouts. This AI-trained model serves as a personalized trainer that can be tweaked to the user's specifications. The AI model assigns a preference category to each workout and notifies the user if it detects a posture issue. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Computer vision

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A recognition technology for the output pattern of likely metamorphic relation of neutron diffusion program 3

A recognition technology for the output pattern of likely me...

引用

3rd international conference on Electronics and Communication;Network and Computer Technology (ECNCT)

作者： Wen, Zhaoyu Yang, Xiaohua Yan, Shiyu Li, Meng Univ South China Sch Comp Sci Hengyang 421001 Peoples R China

ISBN: (数字)9781510652118

ISBN: (纸本)9781510652118;9781510652101

The metamorphic test is a method to alleviate the unexpected value of the Oracle problem. The key point is the identification of the metamorphic relations. The identification of the metamorphic relations of scientific calculation programs is also a complex problem, and the likely of the metamorphic relation of the program can provide enlightening information for the identification of the metamorphic relations. The likely metamorphic relation can be regarded as the implicit expression of the input pattern and output pattern. This paper proposes an output pattern recognition technology based on the likely metamorphic relations of GEP. The technology is mainly aimed at the core neutron diffusion calculation program. The input pattern of the program, and then generate input data and run the program. Finally, in the corresponding output data results, through GEP data mining technology, the output pattern expressed in a variety of functional forms is obtained, which is further compared with analytical solutions and verified to be reliable likely metamorphic relations.

关键词： metamorphic testing metamorphic relation likely metamorphic relation GEP neutron diffusion program

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Quantum Transfer Learning for Enhanced Diabetic Retinopathy Detection Using ResNet Architecture 15th

Quantum Transfer Learning for Enhanced Diabetic Retinopathy ...

引用

15th international conference on Soft Computing and pattern recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Gupta, Vinayak Dash, Yajnaseni Sarangi, Sudhir C. Abraham, Ajith School of Computer Science Engineering and Technology Bennett University UP Greater Noida India School of Artificial Intelligence Bennett University UP Greater Noida India Department of Pharmacology AIIMS New Delhi Delhi India School of Artificial Intelligence Sai University Chennai India

ISBN: (纸本)9783031810794

Diabetic Retinopathy (DR) has emerged as a grave public concern in recent years, which leads to vision impairment and blindness. This progression of DR as a public health concern is because is typically asymptomatic in its early stages therefore making it excruciating to detect in early stages. This study explores the use of ResNet-based Quantum Transfer Learning for DR detection, combining classical deep learning with quantum computing to enhance diagnostic accuracy. This hybrid approach demonstrates the potential of quantum computing to augment deep learning models, particularly in handling intricate medical image data, and contributes to the growing field of quantum-assisted medical diagnostics, offering a novel perspective on the application of quantum computing in healthcare. The model’s design and its performance, shaped by the intricate behavior of quantum systems, pave the way for future research that may refine and expand upon these preliminary insights, ultimately contributing to the evolution of quantum-assisted methodologies in healthcare. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Qubits

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3rd international conference on Next Generation Arithmetic, CoNGA 2022

3rd International Conference on Next Generation Arithmetic, ...

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3rd international conference on Next Generation Arithmetic, CoNGA 2022

ISBN: (纸本)9783031097782

The proceedings contain 8 papers. The special focus in this conference is on Next Generation Arithmetic. The topics include: A Posit8 Decompression Operator for Deep Neural Network Inference;qtorch+: Next Generation Arithmetic for Pytorch machine Learning;ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML;multiPosits: Universal Coding of Rn;comparing Different Decodings for Posit Arithmetic;universal: Reliable, Reproducible, and Energy-Efficient Numerics.

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2021 3rd international conference on Robotics, Intelligent Control and Artificial intelligence, ICRICA 2021

2021 3rd International Conference on Robotics, Intelligent C...

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2021 3rd international conference on Robotics, Intelligent Control and Artificial intelligence, ICRICA 2021

The proceedings contain 94 papers. The topics discussed include: stress analysis of key components of finger rehabilitation exoskeleton robot based on finite element method;design of intelligent wireless laser engraving machine;a flexible under-driven bionic climbing robot design;longitudinal driving force distribution of four in-wheel motors drive electric vehicle based on fuzzy logic;an improved unscented Kalman filter for maneuvering target tracking;path planning of mobile robot based on genetic-ant colony algorithm;design and implementation of intelligent security robot based on lidar and vision fusion;UAV dynamic obstacle avoidance based on improved reciprocal velocity obstacle;and UAV dynamic obstacle avoidance based on improved reciprocal velocity obstacle.

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A Multi-faceted Analytical Approach to Assessing the Economic Impact and Public Sentiment Surrounding COVID-19 in South Asia 15th

A Multi-faceted Analytical Approach to Assessing the Economi...

引用

15th international conference on Soft Computing and pattern recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Dash, Yajnaseni Sood, Aryan Pathak, Shruti Sarangi, Sudhir C. Abraham, Ajith School of Artificial Intelligence Bennett University UP Greater Noida India School of Computer Science Engineering and Technology Bennett University UP Greater Noida India Department of Pharmacology AIIMS New Delhi India School of Artificial Intelligence Sai University Chennai India

ISBN: (纸本)9783031889912

This study examines the economic impact and public sentiment surrounding COVID-19 in ten South Asian countries, utilizing diverse analytical approaches including epidemiological analysis, demographic profiling, and climatic examination. Analyzing the data from reliable sources, the research employs advanced techniques such as the Long Short-Term Memory (LSTM) neural network model and Multiple Criteria decision-making (MCDM) methodologies to discern trends and patterns in the data. The analysis reveals insights into the epidemiological dynamics, demographic vulnerabilities, and climatic influences shaping COVID-19 progression. The present study’s multi-faceted analytical framework underscores the importance of understanding the pandemic’s complexities. The findings can inform evidence-based policy interventions and strategic decision-making processes to mitigate the pandemic’s impact and facilitate regional recovery efforts. Overall, this research aims to provide a thorough understanding of the COVID-19 situation in South Asia and elucidate the effectiveness of different analytical approaches in displaying the complexities of the pandemic. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Global warming

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Question Answering System using NLP and BERT 3

Question Answering System using NLP and BERT

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3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Acharya, Shreya Sornalakshmi, K. Paul, Bidisha Singh, Anshul Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Tamil Nadu India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

This project proposes a simple and smart question answering system using Named Entity recognition (NER) and Bidirectional Encoder Representations from Transformers (BERT) for communication purposes. Communication is a major factor that eases our day-to-day work. In this smart Question answering system, the system will create a customized dataset for the user based on the answers given by the user. Using NER, only the selective answers are taken, i.e., the most important answers, and then updated in the dataset. Based on that dataset, if a person then asks the system a question, the system will use BERT and CDQA (closed domain question answering) to fetch the best answer for the question asked. The resulting system will be an interactive one. © 2022 IEEE.

关键词： Artificial intelligence

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Pedestrian multi-object tracking based on YOLOv7 and BoT-SORT 3

Pedestrian multi-object tracking based on YOLOv7 and BoT-SOR...

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3rd international conference on Computer Vision and pattern Analysis, ICCPA 2023

作者： Li, Tingting Li, Zhanbo Mu, Yuhong Su, Jie School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China School of Cyber Science and Engineering Zhengzhou University Zhengzhou China

ISBN: (纸本)9781510667563

As a crucial component in the realm of computer vision, multi-object tracking has garnered widespread application in areas such as autonomous driving, smart transportation, and surveillance *** on YOLOv7 and BoT-SORT algorithms, this paper followed TBD (track by detection) framework. First, YOLOv7 served as the detector tasked with identifying the target and specifying its location within the frame. Then, the BoT-SORT algorithm was used to track the target based on the target detection results. The results are then tested on the MOT20 dataset. The experimental data show that on MOT20 data set, the accuracy of multi-object tracking reaches 69.36%, and the accuracy of multi-object tracking reaches 79.11%, which effectively solves the problems of target occlusion and frequent identity switching. The experiment proves that it still has good tracking effect under dim lighting and crowded complex scenes. It can achieve better tracking for the non-rigid target of pedestrians, and has higher accuracy than YOLOv7-DeepSORT and YOLOv7-ByteTrack. © 2023 SPIE.

关键词： Target tracking

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