A Comprehensive Review of Recent Research Trends on Unmanned Aerial Vehicles (UAVs)

Systems, Journal Year: 2023, Volume and Issue: 11(8), P. 400 - 400

Published: Aug. 2, 2023

The growing interest in unmanned aerial vehicles (UAVs) from both the scientific and industrial sectors has attracted a wave of new researchers substantial investments this expansive field. However, due to wide range topics subdomains within UAV research, newcomers may find themselves overwhelmed by numerous options available. It is therefore crucial for those involved research recognize its interdisciplinary nature connections with other disciplines. This paper presents comprehensive overview field, highlighting recent trends advancements. Drawing on literature reviews surveys, review begins classifying UAVs based their flight characteristics. then provides an current UAVs, utilizing data Scopus database quantify number documents associated each direction interconnections. also explores potential areas further development including communication, artificial intelligence, remote sensing, miniaturization, swarming cooperative control, transformability. Additionally, it discusses aircraft commonly used control techniques, appropriate algorithms research. Furthermore, addresses general hardware software architecture applications, key issues them. open source projects By presenting view aims enhance our understanding rapidly evolving highly area

Language: Английский

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Deep transfer learning for automatic speech recognition: Towards better generalization

Knowledge-Based Systems, Journal Year: 2023, Volume and Issue: 277, P. 110851 - 110851

Published: July 29, 2023

Language: Английский

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Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review

Journal of Network and Computer Applications, Journal Year: 2023, Volume and Issue: 220, P. 103760 - 103760

Published: Oct. 11, 2023

Language: Английский

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AI in Thyroid Cancer Diagnosis: Techniques, Trends, and Future Directions

Systems, Journal Year: 2023, Volume and Issue: 11(10), P. 519 - 519

Published: Oct. 17, 2023

Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years, offering advanced tools and methodologies that promise to revolutionize patient outcomes. This review provides an exhaustive overview of the contemporary frameworks employed field, focusing on objective AI-driven analysis dissecting across supervised, unsupervised, ensemble learning. Specifically, we delve into techniques such as deep learning, artificial neural networks, traditional classification, probabilistic models (PMs) under supervised With its prowess clustering dimensionality reduction, unsupervised learning (USL) is explored alongside methods, including bagging potent boosting algorithms. The datasets (TCDs) are integral our discussion, shedding light vital features elucidating feature selection extraction critical for diagnostic systems. We lay out standard assessment criteria regression, statistical, computer vision, ranking metrics, punctuating discourse with a real-world example detection using AI. Additionally, this study culminates analysis, current limitations delineating path forward by highlighting open challenges prospective research avenues. Through comprehensive exploration, aim offer readers panoramic view AI’s transformative role diagnosis, underscoring potential pointing toward optimistic future.

Language: Английский

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Face Mask Detection in Smart Cities Using Deep and Transfer Learning: Lessons Learned from the COVID-19 Pandemic

Systems, Journal Year: 2023, Volume and Issue: 11(2), P. 107 - 107

Published: Feb. 17, 2023

After different consecutive waves, the pandemic phase of Coronavirus disease 2019 does not look to be ending soon for most countries across world. To slow spread COVID-19 virus, several measures have been adopted since start outbreak, including wearing face masks and maintaining social distancing. Ensuring safety in public areas smart cities requires modern technologies, such as deep learning transfer learning, computer vision automatic mask detection accurate control whether people wear correctly. This paper reviews progress research, emphasizing techniques. Existing datasets are first described discussed before presenting recent advances all related processing stages using a well-defined taxonomy, nature object detectors Convolutional Neural Network architectures employed their complexity, techniques that applied so far. Moving on, benchmarking results summarized, discussions regarding limitations methodologies provided. Last but least, future research directions detail.

Language: Английский

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Revolutionizing generative pre-traineds: Insights and challenges in deploying ChatGPT and generative chatbots for FAQs

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 246, P. 123224 - 123224

Published: Jan. 19, 2024

Language: Английский

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Automatic speech recognition using advanced deep learning approaches: A survey

Information Fusion, Journal Year: 2024, Volume and Issue: 109, P. 102422 - 102422

Published: April 15, 2024

Language: Английский

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Deep learning for steganalysis of diverse data types: A review of methods, taxonomy, challenges and future directions

Neurocomputing, Journal Year: 2024, Volume and Issue: 581, P. 127528 - 127528

Published: March 6, 2024

Language: Английский

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Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey

Information Fusion, Journal Year: 2024, Volume and Issue: 113, P. 102601 - 102601

Published: July 27, 2024

Language: Английский

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Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion

Artificial Intelligence in Medicine, Journal Year: 2024, Volume and Issue: 155, P. 102935 - 102935

Published: July 26, 2024

Deep learning (DL) in orthopaedics has gained significant attention recent years. Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks, including fracture detection, bone tumour diagnosis, implant recognition, and evaluation osteoarthritis severity. The utilisation is expected increase, owing its ability present accurate diagnoses more efficiently than traditional methods many scenarios. This reduces the time cost diagnosis for patients surgeons. To our knowledge, no exclusive study comprehensively reviewed all aspects currently used practice. review addresses this knowledge gap using articles from Science Direct, Scopus, IEEE Xplore, Web between 2017 2023. authors begin with motivation orthopaedics, enhance treatment planning. then covers various applications detection supraspinatus tears MRI, osteoarthritis, prediction types arthroplasty implants, age assessment, joint-specific soft tissue disease. We also examine challenges implementing scarcity data train lack interpretability, as well possible solutions these common pitfalls. Our work highlights requirements achieve trustworthiness outcomes generated by DL, need accuracy, explainability, fairness models. pay particular fusion techniques one ways increase trustworthiness, which been address multimodality orthopaedics. Finally, we approval set forth US Food Drug Administration enable use applications. As such, aim function guide researchers develop reliable application tasks scratch market.

Language: Английский

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