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Showing 20 of 979 academic articles
Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing
(2019)
Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13640-019-0406-y
Ning Zhang, Enxu Zhang, Fei Li • Applied Sciences
(2023)
Soybean is a type of food crop with economic benefits. Whether they are damaged or not directly affects the survival and nutritional value of soybean plants. In machine learning, unbalanced data represent a major factor affecting machine le...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app13116425
Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies
(2023)
Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/technologies11020055
P. V. Chandrika, Sandeep Kelkar • Advances in medical diagnosis, treatment, and care (AMDTC) book series
(2024)
This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...
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DOI: https://doi.org/10.4018/979-8-3693-1281-0.ch001
Mohammad Mustafa Taye • Computers
(2023)
In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance...
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DOI: https://doi.org/10.3390/computers12050091
Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad-Khasmakhi et al. • ACM Computing Surveys
(2021)
Deep learning--based models have surpassed classical machine learning--based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this art...
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Open Access
DOI: https://doi.org/10.1145/3439726
Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics
(2018)
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...
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DOI: https://doi.org/10.1093/bfgp/ely030
Jin Mo Ahn, Sangsoo Kim, Kwang-Sung Ahn, Sung-Hoon Cho et al. • BMC Ophthalmology
(2019)
Abstract Background This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals. Methods Two hundred and ninety-five images of optic neuropathies, 295 images...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12886-019-1184-0
Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan et al. • BMC Psychiatry
(2025)
Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...
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Open Access (DOAJ)
DOI: 10.1186/s12888-025-07196-2
salma mostafa ahmed helmy, Salsabil Amin, Abeer mahmoud, El-Sayed El-Horabty • International Journal of Intelligent Computing and Information Sciences
(2026)
The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...
DOAJ
Open Access (DOAJ)
DOI: 10.21608/ijicis.2026.442636.1439
Yayin Xu, Ying Zhou, Przemysław Sekuła, Lieyun Ding • Developments in the Built Environment
(2021)
The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...
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DOI: https://doi.org/10.1016/j.dibe.2021.100045
Asmaa Hani Halbouni, Teddy Surya Gunawan, Mohamed Hadi Habaebi, Murad Halbouni et al. • IEEE Access
(2022)
The rapid evolution and growth of the internet through the last decades led to more concern about cyber-attacks that are continuously increasing and changing. As a result, an effective intrusion detection system was required to protect data...
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DOI: https://doi.org/10.1109/access.2022.3151248
Daniel Veltri, Uday Kamath, Amarda Shehu • Bioinformatics
(2018)
Motivation: Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by w...
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DOI: https://doi.org/10.1093/bioinformatics/bty179
PMC: 6084614
Sidrah Liaqat, Kia Dashtipour, Adnan Zahid, Khaled Assaleh et al. • Information
(2020)
The atrial fibrillation (AF) is one of the most well-known cardiac arrhythmias in clinical practice, with a prevalence of 1–2% in the community, which can increase the risk of stroke and myocardial infarction. The detection of AF electrocar...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info11120549
Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri et al. • Journal of King Saud University: Computer and Information Sciences
(2023)
Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...
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Open Access (DOAJ)
DOI: 10.1016/j.jksuci.2022.11.008
Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2017)
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...
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DOI: https://doi.org/10.1109/tnnls.2017.2766168
Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics
(2020)
Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
• De Gruyter eBooks
(2020)
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...
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DOI: https://doi.org/10.1515/9783110670905
Heang‐Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala • Medical Physics
(2020)
Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...
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Open Access
DOI: https://doi.org/10.1002/mp.13764
PMC: 7293164
Iraj Abedi, Mahsa Vali, Bentolhoda Otroshi, Maryam Zamanian et al. • BMC Research Notes
(2024)
Abstract Introduction Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the ...
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Open Access (DOAJ)
DOI: 10.1186/s13104-024-06693-z