A Survey on Deep Learning for Few-Shot PolSAR Image Classification by Ningwei Wang, Weiqiang Jin, Haixia Bi, Chen Xu, Jinghuai Gao

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Exploring the evolution and future prospects of Amharic to English machine translation: a systematic review by Muluken Hussen Asebel, Shimelis Getu Assefa, Mesfin Abebe Haile

“…Pursuable avenues include augmentation of data, tokenization on the language level, and incorporation of linguistic elements into the parallel corpora. …”
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Detection of vehicles and analysis of traffic volume by real-time video-graphic technique using python algorithm by Osman Kantunsung Ramadan, R. Srinivasa Kumar, A. Narender Reddy

“…These statistics showed acceptable reliability levels. The detection data helped PTV Vissim conduct traffic simulations for existing and proposed traffic conditions. …”
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Classifying the Information Needs of Survivors of Domestic Violence in Online Health Communities Using Large Language Models: Prediction Model Development and Evaluation Study by Shaowei Guan, Vivian Hui, Gregor Stiglic, Rose Eva Constantino, Young Ji Lee, Arkers Kwan Ching Wong

“…In addition, we used LLM-based data augmentation techniques to overcome the limitations of a relatively small and imbalanced dataset. …”
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A Retrospective Study of Nonsurgical Management Options for Permanent Filler Complications of the Gluteal Region by Tom S. Decates, MD, PhD, Tamar Schoonen, MD, Armanda J. Onderdijk, MD, PhD, Martin van Leerdam, PhD, Peter J. Velthuis, MD, PhD

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A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection by Rodrigo Colnago Contreras, Monique Simplicio Viana, Victor José Souza Bernardino, Francisco Lledo dos Santos, Önsen Toygar, Rodrigo Capobianco Guido

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Maternal and perinatal outcome in obese pregnant women in labour ward by Zilan Abdullah Hassan, Avin Sadiq Jamil

“…Data were analyzed using the SPSS, version 25, to test statistical significance. …”
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SkinIncept: an ensemble transfer learning-based approach for multiclass skin disease classification using InceptionV3 and InceptionResNetV2 by Md. Hasan Imam Bijoy, Md. Mahbubur Rahman, Abdus Sattar, Aminul Haque, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Tetsuya Shimamura

“…The quality of processed images is validated using statistical methods, including MSE, PSNR, SSIM, and RMSE. …”
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A Hybrid Attention-Based Transformer Model for Arabic News Classification Using Text Embedding and Deep Learning by Md. Mithun Hossain, Md. Shakil Hossain, Mejdl Safran, Sultan Alfarhood, Meshal Alfarhood, M. F. Mridha

“…To deal with the complexities of the Arabic language and enrich the dataset, we used a thorough preparation pipeline that includes text cleaning, tokenization, lemmatization, and data augmentation approaches. We combined a bespoke attention embedder with classic TF-IDF and Bag-of-Words features to provide a comprehensive feature set that includes both the text’s contextual and statistical aspects. …”
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Effectiveness of the Modified WHO Labour Care Guide to Detect Prolonged and Obstructed Labour Among Women Admitted at Eight Publicly Funded, Midwife-Led Community Health Facilities... by Mugyenyi GR, Tumuhimbise W, Atukunda EC, Tibaijuka L, Ngonzi J, Kayondo M, Kanyesigye M, Musimenta A, Yarine FT, Byamugisha JK

“…Data was collected in REDcap and analyzed using STATA v17; statistical significance was p < 0.05.Results: A total of 991 (49.3%) and 1020 (50.7%) women were monitored using the LCG and partograph, respectively. …”
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A Deep Learning-Based Approach for Cell Segmentation in Phase-Contrast Images by Basma A. Mohamed, Nancy M. Salem, Walid Al-Atabany, Lamees N. Mahmoud

“…The Ranger optimizer outperformed Adam and SGD with an Intersection over Union (IoU) of 94.3% and an F1 score of 97.1% on the PhC-C2DH-U373 dataset, as well as an IoU of 85.3% and F1 score of 92% on the PhC-C2DL-PSC dataset, both with data augmentation. Statistical validation using the Wilcoxon signed-rank test confirmed the significance of these results (P-Value &#x003C; 0.01). …”
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Comparative evaluation of deep learning architectures, including UNet, TransUNet, and MIST, for left atrium segmentation in cardiac computed tomography of congenital heart diseases by Seoyeong Yun, Jooyoung Choi

“…Volumes underwent resampling, intensity normalization, and data augmentation. UNet, TransUNet, and MIST models were trained using 80% of 97 cases, with the remaining 20% employed for validation. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…This segmentation is significantly enhanced by runtime data augmentation and trained on a robust train/validation/test dataset split. …”
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Progression of the first stage of spontaneous labour: A prospective cohort study in two sub-Saharan African countries. by Olufemi T Oladapo, Joao Paulo Souza, Bukola Fawole, Kidza Mugerwa, Gleici Perdoná, Domingos Alves, Hayala Souza, Rodrigo Reis, Livia Oliveira-Ciabati, Alexandre Maiorano, Adesina Akintan, Francis E Alu, Lawal Oyeneyin, Amos Adebayo, Josaphat Byamugisha, Miriam Nakalembe, Hadiza A Idris, Ola Okike, Fernando Althabe, Vanora Hundley, France Donnay, Robert Pattinson, Harshadkumar C Sanghvi, Jen E Jardine, Özge Tunçalp, Joshua P Vogel, Mary Ellen Stanton, Meghan Bohren, Jun Zhang, Tina Lavender, Jerker Liljestrand, Petra Ten Hoope-Bender, Matthews Mathai, Rajiv Bahl, A Metin Gülmezoglu

“…Substantial differences exist between actual plots of labour progression of individual women and the 'average labour curves' derived from study population-level data. Exclusion of women with augmented labours from the study population resulted in slightly faster labour progression patterns.…”
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Objective classification for solid hydrometeor particles using deep learning by Asuka Yoshimura, Kazuhisa Tsuboki, Taro Shinoda, Tadayasu Ohigashi, Kensaku Shimizu

“…The results trained using only HYVIS images showed low validity because some types of particles in the training data were insufficient. The data for typical particle shapes were augmented to improve the classification. …”
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Deep learning for automated dental plaque index assessment: validation against expert evaluations by Jin-Sun Jeong, Kyeong-Seop Kim, Yu Gu, Da-Hyun Yoon, Meng Zhang, Ling Wang, Jeong-Hwan Kim

“…Results After data augmentation, the DL model achieved a micro-average accuracy of 73.67% and a macro-average accuracy of 65.15%, with a precision of 76.34%, recall of 65.15%, and an F1 score of 66.15%. …”
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LMVT: A hybrid vision transformer with attention mechanisms for efficient and explainable lung cancer diagnosis by Jesika Debnath, Al Shahriar Uddin Khondakar Pranta, Amira Hossain, Anamul Sakib, Hamdadur Rahman, Rezaul Haque, Md.Redwan Ahmed, Ahmed Wasif Reza, S M Masfequier.Rahman Swapno, Abhishek Appaji

“…This study highlights the potential of hybrid ViT architectures in creating scalable and interpretable data-driven tools for practical use in lung cancer diagnostics.…”
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RiceLeafClassifier‐v1.0: A Quantized Deep Learning Model for Automated Rice Leaf Disease Detection and Edge Deployment by Oluwaseun O. Martins, Christiaan C. Oosthuizen, Dawood A. Desai

“…Training enhancements included data augmentation, dropout, dynamic learning rate scheduling, and early stopping. …”
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Twenty-four-hour profile of peripheral and central blood pressure in young patients with high-normal blood pressure and hypertension by S. B. Silkina, O. N. Antropova, I. V. Osipova

“…Depending on BP, patients were divided into groups: with HNBP and hypertension. Statistical processing and comparative analysis of the obtained data were carried out.Results. …”
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Dependence of local carotid arterial stiffness on the presence of atherosclerotic plaque in the carotid basin in hypertensive patients by A. O. Bohun

“…Basic anthropometric data, laboratory parameters of lipid and carbohydrate metabolism, creatinine, quality intima-media thickness (QIMT), local stiffness indicators: artery diameter, distensibility, distensibility coefficient (DC), compliance coefficient (CC), stiffness indices α, β, local pulse wave velocity (PWV), pressure and augmentation index (using RF-QIMT, RF-QAS technologies) were studied. …”
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