Learning global and local features of power load series through transformer and 2D-CNN: An image-based multi-step forecasting approach incorporating phase …
Z Tang, T Ji, J Kang, Y Huang, W Tang - Applied Energy, 2025 - Elsevier
As modern power systems continue to evolve, accurate power load forecasting remains a
critical issue in energy management. The phase space reconstruction (PSR) method can …
critical issue in energy management. The phase space reconstruction (PSR) method can …
Emphysema subtyping on thoracic computed tomography scans using deep neural networks
Accurate identification of emphysema subtypes and severity is crucial for effective
management of COPD and the study of disease heterogeneity. Manual analysis of …
management of COPD and the study of disease heterogeneity. Manual analysis of …
Semi-supervised COVID-19 volumetric pulmonary lesion estimation on CT images using probabilistic active contour and CNN segmentation
DE Rodriguez-Obregon, AR Mejia-Rodriguez… - … Signal Processing and …, 2023 - Elsevier
Purpose A semi-supervised two-step methodology is proposed to obtain a volumetric
estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods …
estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods …
[HTML][HTML] Modeling Chickpea Productivity with Artificial Image Objects and Convolutional Neural Network
M Bankin, Y Tyrykin, M Duk, M Samsonova, K Kozlov - Plants, 2024 - mdpi.com
The chickpea plays a significant role in global agriculture and occupies an increasing share
in the human diet. The main aim of the research was to develop a model for the prediction of …
in the human diet. The main aim of the research was to develop a model for the prediction of …
Weakly-supervised Segmentation-based Quantitative Characterization of Pulmonary Cavity Lesions in CT Scans
Objective: Pulmonary cavity lesion is one of the commonly seen lesions in lung caused by a
variety of malignant and non-malignant diseases. Diagnosis of a cavity lesion is commonly …
variety of malignant and non-malignant diseases. Diagnosis of a cavity lesion is commonly …
CAM-Guided Translation for Unpaired Weakly-Supervised Medical Image Segmentation
Y Xie, X He, B Yang, F Lyu, S Liu - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Multi-modal learning has shown advantages in improving weakly-supervised medical image
segmentation (WS-MIS). However, most current works are based on paired data, which is …
segmentation (WS-MIS). However, most current works are based on paired data, which is …
Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning
Z Liang, Z Xue, S Rajaraman, Y Feng… - Workshop on Medical …, 2023 - Springer
We proposed a self-supervised machine learning method to automatically rate the severity
of pulmonary edema in the frontal chest X-ray radiographs (CXR) which could be potentially …
of pulmonary edema in the frontal chest X-ray radiographs (CXR) which could be potentially …
Semi-Supervised COVID-19 Volumetric Pulmonary Lesion Estimation on CT Images using Probabilistic Active Contour and CNN Segmentation
L Cendejas-Zaragoza… - Biomedical Signal …, 2023 - europepmc.org
Purpose A semi-supervised two-step methodology is proposed to obtain a volumetric
estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods …
estimation of COVID-19-related lesions on Computed Tomography (CT) images. Methods …
Pulmonary Parenchyma and COVID-19 Lesion Volumetric Segmentation Based
OI Liñan-López¹ - … on Biomedical Engineering: Proceedings of CNIB … - books.google.com
High-resolution computed tomography (HRCT) provides valuable information for the
analysis of COVID-19 patients. For the estimation of the damage caused by this disease …
analysis of COVID-19 patients. For the estimation of the damage caused by this disease …