Thermogram classification using deep siamese network for neonatal disease detection with limited data
Monitoring the body temperatures and evaluating the thermal asymmetry of newborns give
an idea about neonatal diseases. Infrared thermography is a non-invasive, non-harmful, and …
an idea about neonatal diseases. Infrared thermography is a non-invasive, non-harmful, and …
Medical thermograms' classification using deep transfer learning models and methods
Infrared thermal imaging and deep learning provide intelligent monitoring systems that
detect diseases in early phases. However, deep learning models require thousands of …
detect diseases in early phases. However, deep learning models require thousands of …
Health status detection of neonates using infrared thermography and deep convolutional neural networks
Protection of body temperature is critically important for health. Diseases and infections
cause local temperature imbalances in the body. Infrared Thermography (IRT), which is a …
cause local temperature imbalances in the body. Infrared Thermography (IRT), which is a …
Explainable features in classification of neonatal thermograms
Although deep learning models perform high performance classifications (+ 90% accuracy),
there is very limited research on the explanability of models. However, explaining why a …
there is very limited research on the explanability of models. However, explaining why a …
Convolutional neural networks-based approach to detect neonatal respiratory system anomalies with limited thermal image
Respiratory system diseases in neonates are thought-about major causes of neonatal
morbidity and mortality, particularly in developing countries Early diagnosis and …
morbidity and mortality, particularly in developing countries Early diagnosis and …
A deep-learning approach to find respiratory syndromes in infants using thermal imaging
S Navaneeth, S Sarath, BA Nair… - 2020 international …, 2020 - ieeexplore.ieee.org
Respiratory syndromes being one of the most recurrent issues in a neonate, our
methodology involves detection of respiratory rates to identify different types of respiratory …
methodology involves detection of respiratory rates to identify different types of respiratory …
Classification of neonatal diseases with limited thermal Image data
Abstract Evaluation of body temperature and thermal symmetry in neonates is important in
monitoring health conditions and predicting potential risks. With thermography, which is a …
monitoring health conditions and predicting potential risks. With thermography, which is a …
CodCAM: A new ensemble visual explanation for classification of medical thermal images
Early diagnosis systems have vital importance to monitor and follow-up the conditions of
neonates. Thermal imaging as a non-invasive and non-contact method has been used to …
neonates. Thermal imaging as a non-invasive and non-contact method has been used to …
Multi-modal body part segmentation of infants using deep learning
Background Monitoring the body temperature of premature infants is vital, as it allows
optimal temperature control and may provide early warning signs for severe diseases such …
optimal temperature control and may provide early warning signs for severe diseases such …
Classification of medical thermograms belonging neonates by using segmentation, feature engineering and machine learning algorithms
Monitoring and evaluating the skin temperature value are considerably important for
neonates. A system detecting diseases without any harmful radiation in early stages could …
neonates. A system detecting diseases without any harmful radiation in early stages could …