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Titlebook: Applied Computational Technologies; Proceedings of ICCET Brijesh Iyer,Tom Crick,Sheng-Lung Peng Conference proceedings 2022 The Editor(s) (

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期刊全称Applied Computational Technologies
期刊简称Proceedings of ICCET
影响因子2023Brijesh Iyer,Tom Crick,Sheng-Lung Peng
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发行地址Presents research works in the field of applied computational technologies.Provides original works presented at ICCET 2022 held in Lonere, India.Serves as a reference for researchers and practitioners
学科分类Smart Innovation, Systems and Technologies
图书封面Titlebook: Applied Computational Technologies; Proceedings of ICCET Brijesh Iyer,Tom Crick,Sheng-Lung Peng Conference proceedings 2022 The Editor(s) (
影响因子.This book is a collection of best selected research papers presented at 7th International Conference on Computing in Engineering and Technology (ICCET 2022), organized by Dr. Babasaheb Ambedkar Technological University, Lonere, India, during February 12 – 13, 2022. Focusing on frontier topics and next-generation technologies, it presents original and innovative research from academics, scientists, students, and engineers alike. The theme of the conference is Applied Information Processing System..
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Conference proceedings 2022T 2022), organized by Dr. Babasaheb Ambedkar Technological University, Lonere, India, during February 12 – 13, 2022. Focusing on frontier topics and next-generation technologies, it presents original and innovative research from academics, scientists, students, and engineers alike. The theme of the
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2190-3018 ndia.Serves as a reference for researchers and practitioners.This book is a collection of best selected research papers presented at 7th International Conference on Computing in Engineering and Technology (ICCET 2022), organized by Dr. Babasaheb Ambedkar Technological University, Lonere, India, duri
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A Planned Policy for the Designer,es. Additionally, most of the recent deep learning-based approaches have complex network structures. In this work, a simple but optimal deep learning-based convolutional neural network has been developed, which not only performs accurate classification but has also been assessed through standard evaluation measures.
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Engineering Design Applications IVlevel questions. Two integrated deep learning techniques, namely BI-LSTM with attention and BIGRU-CNN with attention, have been implemented for more useful question classification in QAS, and it is observed that BIGRU-CNN with attention gives good performance with an accuracy of 84.5 than BI-LSTM with attention.
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Classification of Traffic Signs Using Deep Learning-Based Approach for Smart Citieses. Additionally, most of the recent deep learning-based approaches have complex network structures. In this work, a simple but optimal deep learning-based convolutional neural network has been developed, which not only performs accurate classification but has also been assessed through standard evaluation measures.
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Attention Based Deep Learning Techniques for Question Classification in Question Answering Systemslevel questions. Two integrated deep learning techniques, namely BI-LSTM with attention and BIGRU-CNN with attention, have been implemented for more useful question classification in QAS, and it is observed that BIGRU-CNN with attention gives good performance with an accuracy of 84.5 than BI-LSTM with attention.
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