Results 81 to 90 of about 7,483 (192)
Machine Learning in Assessing Intraoperative Blood Loss: A Systematic Review and Meta‐Analysis
International Nursing Review, Volume 73, Issue 1, March 2026.ABSTRACT Aim To evaluate the value of machine learning in assessing intraoperative blood loss by comparing associated outcomes with those of the gold standard. Background Intraoperative bleeding is a leading cause of death in surgical patients and may be preventable through early and accurate assessment of blood loss.
Wenlin Zhou +5 more
wiley +1 more source
GT-YOLO: Nearshore Infrared Ship Detection Based on Infrared Images
Journal of Marine Science and EngineeringTraditional visible light target detection is usually applied in scenes with good visibility, while the advantage of infrared target detection is that it can detect targets at nighttime and in harsh weather, thus being able to be applied to ship ...
Yong Wang +3 more
doaj +1 more source
ВПЛИВ РОЗДІЛЬНОЇ ЗДАТНОСТІ ВХІДНИХ ЗОБРАЖЕНЬ НА ПАРАМЕТРИ МОДЕЛЕЙ YOLO ПРИ ДЕТЕКТУВАННІ ОБ’ЄКТІВ
Автоматизация технологических и бизнес-процессовУ статті представлено результати дослідження впливу роздільної здатності вхідних зображень на ключові параметри моделей глибокого навчання YOLOv5 і YOLOv8 при виконанні завдань детектування об’єктів.
Юрій Романович Щебель
doaj +1 more source
Quantized alpha–WIoU YOLOv5 algorithm for rice leaf disease detection
Tạp chí Khoa học và Công nghệThis paper presents an innovative method based on convolutional neural networks for early detection and diagnosis of diseases in rice plants. The YOLOv5n model is modified by replacing its original loss function with the alpha-WIoU function to enhance ...
Nguyen Thu Ha +4 more
doaj +1 more source
Corrugation and Squat Classification and Detection with VGG16 and YOLOv5 Neural Network Models
JOIV: International Journal on Informatics VisualizationRailway track defects in Malaysia pose significant risks of train derailments and accidents, underscoring the urgency for early and accurate defect detection and classification.
Muhammad Syukri Mohd Yazed +5 more
doaj +1 more source
YOLOv5s-GTB: light-weighted and improved YOLOv5s for bridge crack detection
, 2022 In response to the situation that the conventional bridge crack manual detection method has a large amount of human and material resources wasted, this study is aimed to propose a light-weighted, high-precision, deep learning-based bridge apparent crack recognition model that can be deployed in mobile devices' scenarios.
openaire +2 more sources
Journal of Marine Science and EngineeringThe high salinity, humidity, and oxygen-rich environments of coastal marine areas pose serious corrosion risks to metal structures, particularly in equipment such as ships, offshore platforms, and port facilities.
Qifeng Yu +4 more
doaj +1 more source
Coal and gangue segmentation and recognition method based on YOLOv5-SEDC model
Gong-kuang zidonghuaThe existing coal and gangue segmentation and recognition technology has a large number of parameters, slow classification speed, and low recognition accuracy.
YANG Yang +4 more
doaj +1 more source
Measurement and Analysis of Detecting Fish Freshness Levels Using Deep Learning Method
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)Subjective and objective tests used to determine the fish deterioration process require specialized skills and time, making them inefficient for use by the general public in markets.
Dhea Fajriati Anas +2 more
doaj +1 more source
A lightweight personnel detection method for underground coal mines
Meitan kexue jishuThe underground environment of coal mines is complex and has more safety hazards. Personnel detection is an important part of ensuring safe production in coal mines and building smart mines. Commonly used detection algorithms have large parameter counts,
Shuai WANG +4 more
doaj +1 more source