Deep learning modelling techniques: current progress, applications, advantages, and challenges

SF Ahmed, MSB Alam, M Hassan, MR Rozbu… - Artificial Intelligence …, 2023 - Springer
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

Natural language processing advancements by deep learning: A survey

A Torfi, RA Shirvani, Y Keneshloo, N Tavaf… - arXiv preprint arXiv …, 2020 - arxiv.org
Natural Language Processing (NLP) helps empower intelligent machines by enhancing a
better understanding of the human language for linguistic-based human-computer …

Recent advancements in deep learning applications and methods for autonomous navigation: A comprehensive review

AA Golroudbari, MH Sabour - arXiv preprint arXiv:2302.11089, 2023 - arxiv.org
This review article is an attempt to survey all recent AI based techniques used to deal with
major functions in This review paper presents a comprehensive overview of end-to-end …

[HTML][HTML] Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer …

A Bakrania, N Joshi, X Zhao, G Zheng, M Bhat - Pharmacological research, 2023 - Elsevier
Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past
decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of …

A graph neural network (GNN)-based approach for real-time estimation of traffic speed in sustainable smart cities

A Sharma, A Sharma, P Nikashina, V Gavrilenko… - Sustainability, 2023 - mdpi.com
Planning effective routes and monitoring vehicle traffic are essential for creating sustainable
smart cities. Accurate speed prediction is a key component of these efforts, as it aids in …

Improving short text classification with augmented data using GPT-3

SV Balkus, D Yan - Natural Language Engineering, 2022 - cambridge.org
GPT-3 is a large-scale natural language model developed by OpenAI that can perform many
different tasks, including topic classification. Although researchers claim that it requires only …

[PDF][PDF] Detection of citrus leaf diseases using a deep learning technique

AR Luaibi, TM Salman, AH Miry - International Journal of …, 2021 - pdfs.semanticscholar.org
The food security major threats are the diseases affected in plants such as citrus so that the
identification in an earlier time is very important. Convenient malady recognition can assist …

Comparative study of long document classification

V Wagh, S Khandve, I Joshi, A Wani… - TENCON 2021-2021 …, 2021 - ieeexplore.ieee.org
The amount of information stored in the form of documents on the internet has been
increasing rapidly. Thus it has become a necessity to organize and maintain these …

Backdoor attacks and countermeasures in natural language processing models: A comprehensive security review

P Cheng, Z Wu, W Du, G Liu - arXiv preprint arXiv:2309.06055, 2023 - arxiv.org
Deep Neural Networks (DNNs) have led to unprecedented progress in various natural
language processing (NLP) tasks. Owing to limited data and computation resources, using …

A comparative analysis on question classification task based on deep learning approaches

M Zulqarnain, AKZ Alsaedi, R Ghazali… - PeerJ Computer …, 2021 - peerj.com
Question classification is one of the essential tasks for automatic question answering
implementation in natural language processing (NLP). Recently, there have been several …