Intimidate
发表于 2025-3-21 16:10:17
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BULLY
发表于 2025-3-22 00:09:56
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主动
发表于 2025-3-22 00:35:22
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
分开如此和谐
发表于 2025-3-22 05:56:00
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Kidnap
发表于 2025-3-22 10:47:29
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迅速飞过
发表于 2025-3-22 15:57:07
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
大火
发表于 2025-3-22 18:16:25
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.
laparoscopy
发表于 2025-3-23 00:33:01
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.
组装
发表于 2025-3-23 03:06:14
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.
APNEA
发表于 2025-3-23 07:31:16
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.