Detection and classification of COVID-19 by using faster R-CNN and mask R-CNN on CT images
Abstract The coronavirus (COVID-19) pandemic has a devastating impact on people's daily
lives and healthcare systems. The rapid spread of this virus should be stopped by early …
lives and healthcare systems. The rapid spread of this virus should be stopped by early …
Deep learning-based approach for detecting COVID-19 in chest X-rays
ME Sahin - Biomedical Signal Processing and Control, 2022 - Elsevier
Abstract Today, 2019 Coronavirus (COVID-19) infections are a major health concern
worldwide. Therefore, detecting COVID-19 in X-ray images is crucial for diagnosis …
worldwide. Therefore, detecting COVID-19 in X-ray images is crucial for diagnosis …
Image processing and machine learning‐based bone fracture detection and classification using X‐ray images
ME Sahin - International Journal of Imaging Systems and …, 2023 - Wiley Online Library
One of the most important problems in orthopedics is undiagnosed or misdiagnosed bone
fractures. This can lead to patients receiving an incorrect diagnosis or treatment, which can …
fractures. This can lead to patients receiving an incorrect diagnosis or treatment, which can …
Design of efficient methods for the detection of tomato leaf disease utilizing proposed ensemble CNN model
H Ulutaş, V Aslantaş - Electronics, 2023 - mdpi.com
Early diagnosis of plant diseases is of vital importance since they cause social, ecological,
and economic losses. Therefore, it is highly complex and causes excessive workload and …
and economic losses. Therefore, it is highly complex and causes excessive workload and …
Transform and deep learning algorithms for the early detection and recognition of tomato leaf disease
MS Alzahrani, FW Alsaade - Agronomy, 2023 - mdpi.com
Plant diseases pose the greatest threat to food supply integrity, and it is a significant
challenge to identify plant diseases in their earliest stages to reduce the potential for …
challenge to identify plant diseases in their earliest stages to reduce the potential for …
Impact of climatic factors on the prediction of hydroelectric power generation: a deep CNN-SVR approach
M Özbay Karakuş - Geocarto International, 2023 - Taylor & Francis
This study, which aims to make predictions using a previously unused deep hybrid
Convolutional Neural Network-Support Vector Regression approach for hydropower …
Convolutional Neural Network-Support Vector Regression approach for hydropower …
A Deep Learning-Based Technique for Diagnosing Retinal Disease by Using Optical Coherence Tomography (OCT) Images
ME Şahin - Turkish Journal of Science and Technology, 2022 - dergipark.org.tr
The retina layer is the most complex and sensitive part of the eye, and disorders that affect it
have a big impact on people's lives. The Optical Coherence Tomography (OCT) imaging …
have a big impact on people's lives. The Optical Coherence Tomography (OCT) imaging …
Research and Development of Deep Learning Algorithms for the Classification of Pneumonia Type and Detection of Ground-Glass Loci on Radiological Images
AV Emchinov, VV Ryazanov - Pattern Recognition and Image Analysis, 2022 - Springer
Pneumonia is a highly dangerous state that poses serious risks to the health of a patient. In
contrast to common pneumonia, lung disease COVID-19 causes a large number of lethal …
contrast to common pneumonia, lung disease COVID-19 causes a large number of lethal …