Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...
Abstract: Accurate segmentation of cardiac structures in echocardiographic images plays a vital role in the quantitative assessment of cardiac function, enabling early detection and management of ...
Abstract: Test-Time Adaptation (TTA) offers a practical solution for deploying image segmentation models under domain shift without accessing source data or retraining. Among existing TTA strategies, ...
Abstract: Bearing fault diagnosis is a critical task for ensuring the safe operation of industrial equipment. However, traditional methods suffer from low fault identification accuracy and ...
Abstract: The contributions of Optuna in optimizing CNNs on CIFAR-10 increase model performance by a remarkable extent. It runs gradient boosting machines against linear models of regression to check ...
Abstract: Improving the resolution of medical images is an important task in ensuring trustworthy diagnosis and effective monitoring of diseases. Of the newest deep learning algorithms, Convolutional ...
Abstract: In this paper, we proposed a novel deep learning framework, the Synergistic Deep Learning Model, for recognizing copyrighted characters with heightened accuracy and minimized overfitting.
Abstract: Remote sensing semantic segmentation (RSSS) remains challenged by semantic inconsistency, where spatially contiguous objects of the same category are fragmented into conflicting labels, and ...
EDITOR’S NOTE: Call to Earth is a CNN editorial series committed to reporting on the environmental challenges facing our planet, together with the solutions. Rolex’s Perpetual Planet Initiative has ...
Abstract: Accurate acquisition of wound area is crucial for clinical evaluation and monitoring the healing process in wound research. However, traditional methods relying on manual measurement and ...
Abstract: Retinal diseases such as papilledema, tortuosity, and glaucoma are major contributors to preventable blindness, yet they are often not diagnosed until they are in advanced stages due to ...
Abstract: Stroke detection from medical imaging, which is essential for early diagnosis and prompt intervention, greatly impacts patient outcomes. In this study, provide a technique that uses ...
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