Neural networks : the official journal of the International Neural Network Society
Jul 30, 2024
Unsupervised domain adaptation (UDA) is a weakly supervised learning technique that classifies images in the target domain when the source domain has labeled samples, and the target domain has unlabeled samples. Due to the complexity of imaging condi...
Neural networks : the official journal of the International Neural Network Society
Jul 30, 2024
Most existing model-based and learning-based image deblurring methods usually use synthetic blur-sharp training pairs to remove blur. However, these approaches do not perform well in real-world applications as the blur-sharp training pairs are diffic...
Neural networks : the official journal of the International Neural Network Society
Jul 30, 2024
This article mainly centers on proposing new fixed-time (FXT) stability lemmas of discontinuous systems, in which novel optimization approaches are utilized and more relaxed conditions are required. The conventional discussions about Vt>1 and 0
PURPOSE: Diagnosing pulmonary embolism (PE) is still challenging due to other conditions that can mimic its appearance, leading to incomplete or delayed management and several inter-observer variabilities. This study evaluated the performance and cli...
This study evaluates the performance of three typical convolutional neural network based deep learning algorithms for oil spill detection using medium-resolution optical satellite imagery from Sentinel-2 MSI, Landsat-8 OLI, and Landsat-9 OLI2. Oil sl...
Archives of gynecology and obstetrics
Jul 30, 2024
BACKGROUND: We aimed to develop novel artificial intelligence (AI) models based on early pregnancy features to forecast the likelihood of recurrent gestational diabetes mellitus (GDM) before 14 weeks of gestation in subsequent pregnancies.
Journal of applied clinical medical physics
Jul 30, 2024
BACKGROUND: Data collected from hospitals are usually partially annotated by radiologists due to time constraints. Developing and evaluating deep learning models on these data may result in over or under estimation PURPOSE: We aimed to quantitatively...
Medical imaging is indispensable for accurate diagnosis and effective treatment, with modalities like MRI and CT providing diverse yet complementary information. Traditional image fusion methods, while essential in consolidating information from mult...
The process of brain tumour segmentation entails locating the tumour precisely in images. Magnetic Resonance Imaging (MRI) is typically used by doctors to find any brain tumours or tissue abnormalities. With the use of region-based Convolutional Neur...
Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effe...
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