Fault detection and computation of power in PV cells under faulty conditions using deep-learning
Energy Reports, 2023 Renewable energy is considered to be an alternate option for limiting the consumption of fossil fuel along with reducing environmental pollution. Among the possible renewable energy resources, solar energy is considered to be the key candidate as it is ...
Amir Sohail +5 more
doaj +1 more source
Automated detection and segmentation of pleural effusion on ultrasound images using an Attention U-net. [PDF]
J Appl Clin Med Phys, 2023 BackgroundUltrasonic for detecting and evaluating pleural effusion is an essential part of the Extended Focused Assessment with Sonography in Trauma (E-FAST) in emergencies. Our study aimed to develop an Artificial Intelligence (AI) diagnostic model that
Huang L +7 more
europepmc +2 more sources
Journal of Associated Medical SciencesBackground: The contour of the high-risk clinical target volume (HR-CTV) is important in computed tomography (CT)-based cervical cancer brachytherapy to ensure adequate target tumor coverage while sparing radiation exposure to organs at risk (OARs ...
Thinnagit Srikhot +3 more
doaj +1 more source
Attention-guided hierarchical fusion U-Net for uncertainty-driven medical image segmentation [PDF]
Attention-guided hierarchical fusion U-Net for uncertainty-driven medical image ...
AF Frangi (7552415) +8 more
core +2 more sources
AResU-Net: Attention Residual U-Net for Brain Tumor Segmentation
, 2020 Automatic segmentation of brain tumors from magnetic resonance imaging (MRI) is a challenging task due to the uneven, irregular and unstructured size and shape of tumors.
Hengbo Zhang +3 more
core +1 more source
U-Net Transformer: Self and Cross Attention for Medical Image Segmentation
, 2021 International audienceMedical image segmentation remains particularly challenging for complex and low-contrast anatomical structures. In this paper, we introduce the U-Transformer network, which combines a U-shaped architecture for image segmentation ...
Rambour, Clement +5 more
core +2 more sources
Clinically Interpretable Nuclei Segmentation for Robust Histopathological Image Analysis
Applied SciencesBackground/Objectives: Accurate nuclear segmentation is a fundamental step in computational pathology, enabling reliable estimation of cellularity and nuclear morphology. However, segmentation models are typically evaluated under ideal imaging conditions,
Liana Stanescu, Cosmin Stoica Spahiu
doaj +1 more source
SEGMENTATION OF CANCER MASSES ON BREAST ULTRASOUND IMAGES USING MODIFIED U-NET
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2023 Breast cancer causes a huge number of women’s deaths every year. The accurate localization of a breast lesion is a crucial stage. The segmentation of breast ultrasound images participates in the improvement of the process of detection of breast ...
Ihssane Khallassi +2 more
doaj +1 more source
Light U-Net with a New Morphological Attention Gate Model Application to Analyse Wood Sections
, 2023 International audienceThis article focuses on heartwood segmentation from cross-section RGB images (see Fig.1). In this context, we propose a novel attention gate (AG) model for both improving performance and making light convolutional neural networks ...
Ngo, Phuc +4 more
core +1 more source
Multichannel seismic impedance inversion based on Attention U-Net
Frontiers in Earth Science, 2023 Recently, seismic inversion has made extensive use of supervised learning methods. The traditional deep learning inversion network can utilize the temporal correlation in the vertical direction.
Juan Ning +4 more
doaj +1 more source