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Academic Articles & Research Papers
Showing 20 of 25 academic articles
Amna Ikram, Azhar Imran • Informatics in Medicine Unlocked
(2026)
Diabetic Retinopathy (DR) is a major complication of diabetes that can result in irreversible vision loss if not detected early. Manual ophthalmologic screening is time-consuming and subject to subjectivity, underscoring the need for accura...
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Open Access (DOAJ)
DOI: 10.1016/j.imu.2026.101744
Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jong‐Seok Lee et al. • Artificial Intelligence Review
(2023)
Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...
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DOI: https://doi.org/10.1007/s10462-023-10562-9
Mahmoud S. Mayaleh, Samer A. Mayaleh • Discover Artificial Intelligence
(2026)
Abstract Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models. This study evaluates and compares the effectiveness of three data augmentation strategies: Easy Data Augm...
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Open Access (DOAJ)
DOI: 10.1007/s44163-025-00813-9
Lucas Francisco Amaral Orosco Pellicer, Taynan Maier Ferreira, Anna Helena Reali Costa • Applied Soft Computing
(2022)
Data Augmentation (DA) methods – a family of techniques designed for synthetic generation of training data – have shown remarkable results in various Deep Learning and Machine Learning tasks. Despite its widespread and successful adoption w...
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DOI: https://doi.org/10.1016/j.asoc.2022.109803
Miao Jiang, Honghui Chen • Applied Sciences
(2025)
Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine tran...
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Open Access (DOAJ)
DOI: 10.3390/app15052521
Bohan Li, Yutai Hou, Wanxiang Che • AI Open
(2022)
As an effective strategy, data augmentation (DA) alleviates data scarcity scenarios where deep learning techniques may fail. It is widely applied in computer vision then introduced to natural language processing and achieves improvements in...
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DOI: https://doi.org/10.1016/j.aiopen.2022.03.001
Zahraa Tarek, Esraa Hasan • Journal of the Saudi Society of Agricultural Sciences
(2026)
Abstract Self-supervised learning (SSL) has emerged as a pivotal paradigm in computer vision, particularly for applications where labeled data are limited, costly, or labor-intensive to obtain. This paradigm is especially relevant to sustai...
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Open Access (DOAJ)
DOI: 10.1007/s44447-026-00151-x
Hairui Zhu, Shanhong Guo, Weixing Sheng, Lei Xiao • Remote Sensing
(2023)
Ship classification technology using synthetic aperture radar (SAR) has become a research hotspot. Many deep-learning-based methods have been proposed with handcrafted models or using transplanted computer vision networks. However, most of ...
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Open Access (DOAJ)
DOI: 10.3390/rs15112904
Paulo Monteiro de Carvalho Monson, Vinicius Augusto Dare de Almeida, Gabriel Augusto David, Pedro Oliveira Conceição Junior et al. • Engineering Proceedings
(2024)
Computer vision applications demand a significant amount of data for effective training and inference in many computer vision tasks. However, data insufficiency situations usually happen due to multiple reasons, resulting in computational m...
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Open Access (DOAJ)
DOI: 10.3390/ecsa-11-20476
Nino Cauli, Diego Reforgiato Recupero • Future Internet
(2022)
In most Computer Vision applications, Deep Learning models achieve state-of-the-art performances. One drawback of Deep Learning is the large amount of data needed to train the models. Unfortunately, in many applications, data are difficult ...
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Open Access (DOAJ)
DOI: 10.3390/fi14030093
Kota Suzuki, Abu Saleh Musa Miah, Jungpil Shin • Sensors
(2025)
Eye-tracking technology enables communication for individuals with muscle control difficulties, making it a valuable assistive tool. Traditional systems rely on electrooculography (EOG) or infrared devices, which are accurate but costly and...
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Open Access (DOAJ)
DOI: 10.3390/s25206325
Vinodkumar Patil, Manisha Patil, Smital Patil, Satish Desale • Advances in Engineering and Intelligence Systems
(2026)
Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...
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Open Access (DOAJ)
DOI: 10.22034/aeis.2026.570662.1424
B. Valarmathi, N. Srinivasa Gupta, G. Prakash, R. Hemadri Reddy et al. • IEEE Access
(2023)
Deep learning and computer vision algorithms will be applied to find the breed of the dog from an image. The goal is to have the user submit an image of a dog, and the model will choose one of the 120 breeds stated in the dataset to determi...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3297440
Tryan Aditya Putra, Syahidah Izza Rufaida, Jenq-Shiou Leu • IEEE Access
(2020)
In recent years, deep learning has taken the spotlight in automated medical bioimaging. However, the performance of current state-of-the-art score stems primarily from well-tuned parameters and architecture. There is still only limited rese...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.2976045
Om Khare, Sunil Mane, Harshmohan Kulkarni, Ninad Barve • Discover Artificial Intelligence
(2024)
Abstract Plant diseases significantly threaten global agriculture, impacting crop yield and food security. Nearly 30% of the crop yield is lost due to plant diseases. Efficient identification and classification of plant diseases through com...
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Open Access (DOAJ)
DOI: 10.1007/s44163-024-00150-3
Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences
(2025)
In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...
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Open Access (DOAJ)
DOI: 10.3390/app15031552
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
Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports
(2025)
Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-28268-z
Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang et al. • IET Image Processing
(2022)
Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation us...
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DOI: https://doi.org/10.1049/ipr2.12419
Lisi Zhang, Qiancheng Yu, Beijing Zhou, Yifan Zhang et al. • IEEE Access
(2023)
The efficacy of credit risk assessment models is pivotal to the risk management capacity of financial institutions. Traditional credit risk models often suffer from inadequate predictive accuracy due to overlooked feature combinations and w...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3322429