Role of deep learning in brain tumor detection and classification (2015 to 2020): A review
During the last decade, computer vision and machine learning have revolutionized the world
in every way possible. Deep Learning is a sub field of machine learning that has shown …
in every way possible. Deep Learning is a sub field of machine learning that has shown …
Multimodal brain tumor classification using deep learning and robust feature selection: A machine learning application for radiologists
Manual identification of brain tumors is an error-prone and tedious process for radiologists;
therefore, it is crucial to adopt an automated system. The binary classification process, such …
therefore, it is crucial to adopt an automated system. The binary classification process, such …
A novel approach based on integration of convolutional neural networks and deep feature selection for short-term solar radiation forecasting
H Acikgoz - Applied Energy, 2022 - Elsevier
In this study, a novel deep solar forecasting approach is proposed based on the complete
ensemble empirical mode decomposition with adaptive noise (CEEMDAN), continuous …
ensemble empirical mode decomposition with adaptive noise (CEEMDAN), continuous …
A review paper about deep learning for medical image analysis
B Sistaninejhad, H Rasi, P Nayeri - … and Mathematical Methods …, 2023 - Wiley Online Library
Medical imaging refers to the process of obtaining images of internal organs for therapeutic
purposes such as discovering or studying diseases. The primary objective of medical image …
purposes such as discovering or studying diseases. The primary objective of medical image …
Efficient framework for brain tumour classification using hierarchical deep learning neural network classifier
In this manuscript, an efficient framework is proposed for brain tumour classification (BTC)
based on hierarchical deep-learning neural network (HieDNN) classifier. Here, the input …
based on hierarchical deep-learning neural network (HieDNN) classifier. Here, the input …
Towards effective classification of brain hemorrhagic and ischemic stroke using CNN
Brain stroke is one of the most leading causes of worldwide death and requires proper
medical treatment. Therefore, in this paper, our aim is to classify brain computed tomography …
medical treatment. Therefore, in this paper, our aim is to classify brain computed tomography …
A new deep CNN model for environmental sound classification
Cognitive prediction in the complicated and active environments is of great importance role
in artificial learning. Classification accuracy of sound events has a robust relation with the …
in artificial learning. Classification accuracy of sound events has a robust relation with the …
Optimized deep learning architecture for brain tumor classification using improved Hunger Games Search Algorithm
MM Emam, NA Samee, MM Jamjoom… - Computers in Biology …, 2023 - Elsevier
One of the worst diseases is a brain tumor, which is defined by abnormal development of
synapses in the brain. Early detection of brain tumors is essential for improving prognosis …
synapses in the brain. Early detection of brain tumors is essential for improving prognosis …
Survey of supervised learning for medical image processing
A Aljuaid, M Anwar - SN Computer Science, 2022 - Springer
Medical image interpretation is an essential task for the correct diagnosis of many diseases.
Pathologists, radiologists, physicians, and researchers rely heavily on medical images to …
Pathologists, radiologists, physicians, and researchers rely heavily on medical images to …
Brain stroke classification and segmentation using encoder-decoder based deep convolutional neural networks
Accurate diagnosis of brain stroke, classification and segmentation of the stroke are
extremely important for physicians to focus on specific points of the brain and apply the right …
extremely important for physicians to focus on specific points of the brain and apply the right …