A survey on deep learning-based change detection from high-resolution remote sensing images

H Jiang, M Peng, Y Zhong, H Xie, Z Hao, J Lin, X Ma… - Remote Sensing, 2022 - mdpi.com
Change detection based on remote sensing images plays an important role in the field of
remote sensing analysis, and it has been widely used in many areas, such as resources …

Deep learning in ECG diagnosis: A review

X Liu, H Wang, Z Li, L Qin - Knowledge-Based Systems, 2021 - Elsevier
Cardiovascular disease (CVD) is a general term for a series of heart or blood vessels
abnormality that serves as a global leading reason for death. The earlier the abnormal heart …

Stages-based ECG signal analysis from traditional signal processing to machine learning approaches: A survey

M Wasimuddin, K Elleithy, AS Abuzneid… - IEEE …, 2020 - ieeexplore.ieee.org
Electrocardiogram (ECG) gives essential information about different cardiac conditions of
the human heart. Its analysis has been the main objective among the research community to …

Automated detection of coronary artery disease, myocardial infarction and congestive heart failure using GaborCNN model with ECG signals

V Jahmunah, EYK Ng, TR San, UR Acharya - Computers in biology and …, 2021 - Elsevier
Cardiovascular diseases (CVDs) are main causes of death globally with coronary artery
disease (CAD) being the most important. Timely diagnosis and treatment of CAD is crucial to …

Deep learning-based ECG arrhythmia classification: A systematic review

Q Xiao, K Lee, SA Mokhtar, I Ismail, ALM Pauzi… - Applied Sciences, 2023 - mdpi.com
Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …

A review of plant phenotypic image recognition technology based on deep learning

J Xiong, D Yu, S Liu, L Shu, X Wang, Z Liu - Electronics, 2021 - mdpi.com
Plant phenotypic image recognition (PPIR) is an important branch of smart agriculture. In
recent years, deep learning has achieved significant breakthroughs in image recognition …

Deep learning models for classification of red blood cells in microscopy images to aid in sickle cell anemia diagnosis

L Alzubaidi, MA Fadhel, O Al-Shamma, J Zhang… - Electronics, 2020 - mdpi.com
Sickle cell anemia, which is also called sickle cell disease (SCD), is a hematological
disorder that causes occlusion in blood vessels, leading to hurtful episodes and even death …

Optimizing the performance of breast cancer classification by employing the same domain transfer learning from hybrid deep convolutional neural network model

L Alzubaidi, O Al-Shamma, MA Fadhel, L Farhan… - Electronics, 2020 - mdpi.com
Breast cancer is a significant factor in female mortality. An early cancer diagnosis leads to a
reduction in the breast cancer death rate. With the help of a computer-aided diagnosis …

Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017–2023

Y Ansari, O Mourad, K Qaraqe, E Serpedin - Frontiers in Physiology, 2023 - frontiersin.org
Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography
(ECG) still represents the benchmark approach for identifying cardiac irregularities …

[HTML][HTML] Robust detection of atrial fibrillation from short-term electrocardiogram using convolutional neural networks

S Nurmaini, AE Tondas, A Darmawahyuni… - Future Generation …, 2020 - Elsevier
The most prevalent arrhythmia observed in clinical practice is atrial fibrillation (AF). AF is
associated with an irregular heartbeat pattern and a lack of a distinct P-waves signal. A low …