A systematic review of effective data augmentation in cervical cancer detection by Betelhem Zewdu Wubineh, Andrzej Rusiecki, Krzysztof Halawa

“…This review examines effective augmentation techniques and top-performing deep-learning models for segmentation and classification in cervical cancer detection. …”
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Hand Washing Gesture Recognition Using Synthetic Dataset by Rüstem Özakar, Eyüp Gedikli

“…Using this dataset, four neural network models, Inception-V3, Yolo-8n, Yolo-8n segmentation and PointNet, were trained for gesture classification. …”
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Evaluating the Robustness of Foundation Models for Satellite Imagery by Gilbert Rotich, Sudeep Sarkar

“…Currently, the usefulness of the majority of thesemodels presented in their respective works are demonstrated using one or two downstream tasks, specifically classification and segmentation using limited datasets that lack complexity based on the diversity of scenes, resolution, and sizes. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…The integration of advanced models, YOLOv11 for detection, HRNet for segmentation, Deep SORT for tracking, CSRNet for counting, LSTM for trajectory prediction, and Vision Transformers for classification enables the framework to maintain high accuracy even under challenging conditions like occlusion, variable lighting, and scale variations.DiscussionThe outcomes show that the chosen deep learning system is powerful enough to deal with the challenges of aerial vehicle analysis and gives reliable and precise results in all the aforementioned tasks. …”
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The role of advanced machine learning in COVID-19 medical imaging: A technical review by Abdul Muiz Fayyaz, Said Jadid Abdulkadir, Shahab Ul Hassan, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, Lareib Fatima Talib

“…The study reviews key research on ML-based COVID-19 classification, focusing on stages like preprocessing, segmentation, feature extraction, transfer learning, feature selection, and classification. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. …”
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Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

“…Data processing consists of preprocessing for segmentation of the leaf area, feature extraction, classification and subsequent analysis of relevance of spectral bands. …”
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AI in Endoscopic Gastrointestinal Diagnosis: A Systematic Review of Deep Learning and Machine Learning Techniques by Jovita Relasha Lewis, Sameena Pathan, Preetham Kumar, Cifha Crecil Dias

“…It provides a detailed analysis of Machine learning (ML) techniques like preprocessing, segmentation, feature extraction, and classification. …”
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Deep learning-based interpretable prediction of recurrence of diffuse large B-cell lymphoma by Hussein Naji, Paul Hahn, Juan I. Pisula, Stefano Ugliano, Adrian Simon, Reinhard Büttner, Katarzyna Bozek

“…We utilized attention-based classification to highlight areas within the images that were of high relevance for the model’s classification. …”
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Improvement in Accuracy and Concordance of American Society of Anesthesiologist’s Physical Status (ASA-PS) Scoring Assignment over a 11 Year Time Period Using Patient BMI as a Como... by Matthew W. Dyer, Benjamin T. Kor, Nathan T. Kor, Andrew C. Hanson, Jennifer J. Kor, Todd M. Kor, Thomas M. Stewart, Hans P. Sviggum

“…After attaining IRB approval, all eligible patients over the age of 18 who had surgical procedures under general anesthesia at Mayo Clinic in Rochester, MN, between January 1, 2010, and December 31, 2020, were retrospectively analyzed. A segmented logistic regression model was used to estimate the trends (per-year change in odds) of ASA under classification according to severity of obesity during 3 epochs: preimplementation (2010–2014), implementation (2015), and postimplementation (2016–2020). …”
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Deep learning analysis for rheumatologic imaging: current trends, future directions, and the role of human by Jucheol Moon, Pratik Jadhav, Sangtae Choi

“…Convolutional neural networks, a DL model type, have shown great potential in medical image classification, segmentation, and anomaly detection, often surpassing human performance in tasks like tumor identification and disease severity grading. …”
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Remote Assistance for Bone-Fractured Patients using Deep Learning Models by Nallakaruppan Kailasanathan, Sivaramakrishnan Somayaji, Mohamed Baza, Gautam Srivastava, SenthilKumaran Ulaganathan, Gokul Yenduri, Vaishali Ravindranath, Maazen Alsabaan

“…Object detection techniques are also introduced for detecting minor fractures using region-based image segmentation, ensuring precise diagnosis even for subtle injuries. …”
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Depression Recognition Using Daily Wearable-Derived Physiological Data by Xinyu Shui, Hao Xu, Shuping Tan, Dan Zhang

“…Utilizing a Random Forest algorithm, we distinguished depressive and non-depressive individuals with varying classification accuracies on data aggregated over 6 h, 2 h, 30 min, and 5 min segments, as 90.0%, 84.7%, 80.1%, and 76.0%, respectively. …”
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Federated LeViT-ResUNet for Scalable and Privacy-Preserving Agricultural Monitoring Using Drone and Internet of Things Data by Mohammad Aldossary, Jaber Almutairi, Ibrahim Alzamil

“…The suggested approach improves on conventional models like ResNet, DenseNet, and the vision transformer with a 98.9% classification accuracy and 99.3% AUC. …”
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Viper Venom and Synthetic Peptides: Emerging Active Ingredients in Anti-Ageing Cosmeceuticals by Dana Georgiana Moisă, Anca Maria Juncan, Luca-Liviu Rus, Andreea Loredana Vonica-Țincu, Gabriela Cormoș, Felicia Gabriela Gligor

“…The study provided an extensive background considering the market segmentation of viper venom-based and synthetic peptide-based cosmetics, including 245 cosmetics (70 manufacturers), also including the classification into Mass-Market and Premium-Market segments, which adds practical value. …”
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Feature Extraction of Plant Leaf Using Deep Learning by Muhammad Umair Ahmad, Sidra Ashiq, Gran Badshah, Ali Haider Khan, Muzammil Hussain

“…However, leaves are an effective means of differentiating plant species because of their unique characteristics like area, diameter, perimeter, circularity, aspect ratio, solidity, eccentricity, and narrow factor. …”
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Review on the current trends in tongue diagnosis systems by Chang Jin Jung, Young Ju Jeon, Jong Yeol Kim, Keun Ho Kim

“…These systems consist of hardware including cameras, light sources, and a ColorChecker, and software for color correction, segmentation of tongue region, and tongue classification. …”
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Dense skip-attention for convolutional networks by Wenjie Liu, Guoqing Wu, Han Wang, Fuji Ren

“…The experimental results demonstrate that our method improves the performance of existing attention mechanism methods, such as Squeeze-and-Excitation Networks, Efficient Channel Attention Networks and Convolutional Block Attention Module, in tasks like image classification, object detection, and instance segmentation. …”
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Optimizing FCN for devices with limited resources using quantization and sparsity enhancement by Muhammad Faizan-Khan, Nisar Ali, Raja Hashim Ali, Areej Alasiry, Mehrez Marzougui, Shabbab Ali Algamdi, Yunyoung Nam

“…The findings highlight the efficacy of full-layer quantization and retraining in simultaneously reducing network complexity and maintaining accuracy in both image classification and semantic segmentation tasks.…”
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VBNet: A Visually-Aware Biomimetic Network for Simulating the Human Eye’s Visual System by Zhaofei Li, Yufan Mao, Mingshan Zhong, Jun Zhao

“…Empirical results highlight VBNet’s superiority over RegNet and PVT in ImageNet classification and competitive performance in MSCOCO object detection and instance segmentation. …”
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