Related references
Note: Only part of the references are listed.COVID-19 Diagnosis from Chest X-ray Images Using a Robust Multi-Resolution Analysis Siamese Neural Network with Super-Resolution Convolutional Neural Network
Happy Nkanta Monday et al.
DIAGNOSTICS (2022)
Multi-Modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training
Jong Hak Moon et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2022)
Chest X-ray analysis empowered with deep learning: A systematic review
Dulani Meedeniya et al.
APPLIED SOFT COMPUTING (2022)
A TRANSFORMER-BASED SIAMESE NETWORK FOR CHANGE DETECTION
Wele Gedara Chaminda Bandara et al.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) (2022)
CMT: Convolutional Neural Networks Meet Vision Transformers
Jianyuan Guo et al.
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2022)
U-Net Based Chest X-ray Segmentation with Ensemble Classification for Covid-19 and Pneumonia
K. A. S. H. Kumarasinghe et al.
INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING (2022)
TEMDnet: A Novel Deep Denoising Network for Transient Electromagnetic Signal With Signal-to-Image Transformation
Kecheng Chen et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2022)
COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization
Tahmina Zebin et al.
APPLIED INTELLIGENCE (2021)
Covid-19 detection via deep neural network and occlusion sensitivity maps
Muhammad Aminu et al.
ALEXANDRIA ENGINEERING JOURNAL (2021)
SUNet: Change Detection for Heterogeneous Remote Sensing Images from Satellite and UAV Using a Dual-Channel Fully Convolution Network
Ruizhe Shao et al.
REMOTE SENSING (2021)
COVID-19 in CXR: From Detection and Severity Scoring to Patient Disease Monitoring
Maayan Frid-Adar et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)
An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research
Sungchul Kim et al.
KOREAN JOURNAL OF RADIOLOGY (2021)
Deep-learning framework to detect lung abnormality - A study with chest X-Ray and lung CT scan images
Abhir Bhandary et al.
PATTERN RECOGNITION LETTERS (2020)
Automated abnormality classification of chest radiographs using deep convolutional neural networks
Yu-Xing Tang et al.
NPJ DIGITAL MEDICINE (2020)
Utilizing Knowledge Distillation in Deep Learning for Classification of Chest X-Ray Abnormalities
Thi Kieu Khanh Ho et al.
IEEE ACCESS (2020)
Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges
Mohammad Hesam Hesamian et al.
JOURNAL OF DIGITAL IMAGING (2019)
Building Instance Change Detection from Large-Scale Aerial Images using Convolutional Neural Networks and Simulated Samples
Shunping Ji et al.
REMOTE SENSING (2019)
Deep learning in chest radiography: Detection of findings and presence of change
Ramandeep Singh et al.
PLOS ONE (2018)
Change Detection Based on Multi-Feature Clustering Using Differential Evolution for Landsat Imagery
Mi Song et al.
REMOTE SENSING (2018)
Is post-pneumonia chest X-ray for lung malignancy useful? Results of an audit of current practice
C. Macdonald et al.
INTERNAL MEDICINE JOURNAL (2015)
Contribution of routine chest x-ray in the long-term follow-up of patients with differentiated thyroid carcinoma
MA Habra et al.
THYROID (2006)
Routine chest radiography in a primary care setting
S Tigges et al.
RADIOLOGY (2004)