A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
[HTML][HTML] A review on brain tumor segmentation based on deep learning methods with federated learning techniques
Brain tumors have become a severe medical complication in recent years due to their high
fatality rate. Radiologists segment the tumor manually, which is time-consuming, error …
fatality rate. Radiologists segment the tumor manually, which is time-consuming, error …
MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques
Background Detecting brain tumors in their early stages is crucial. Brain tumors are
classified by biopsy, which can only be performed through definitive brain surgery …
classified by biopsy, which can only be performed through definitive brain surgery …
MRI-based brain tumor classification using ensemble of deep features and machine learning classifiers
Brain tumor classification plays an important role in clinical diagnosis and effective
treatment. In this work, we propose a method for brain tumor classification using an …
treatment. In this work, we propose a method for brain tumor classification using an …
A hybrid CNN-SVM threshold segmentation approach for tumor detection and classification of MRI brain images
Objective In this research paper, the brain MRI images are going to classify by considering
the excellence of CNN on a public dataset to classify Benign and Malignant tumors …
the excellence of CNN on a public dataset to classify Benign and Malignant tumors …
Multi-modal brain tumor detection using deep neural network and multiclass SVM
Background and Objectives: Clinical diagnosis has become very significant in today's health
system. The most serious disease and the leading cause of mortality globally is brain cancer …
system. The most serious disease and the leading cause of mortality globally is brain cancer …
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 …
Deep learning for multigrade brain tumor classification in smart healthcare systems: A prospective survey
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade
recognition is a challenging problem for radiologists in health monitoring and automated …
recognition is a challenging problem for radiologists in health monitoring and automated …
Classification of brain tumors from MRI images using a convolutional neural network
MM Badža, MČ Barjaktarović - Applied Sciences, 2020 - mdpi.com
The classification of brain tumors is performed by biopsy, which is not usually conducted
before definitive brain surgery. The improvement of technology and machine learning can …
before definitive brain surgery. The improvement of technology and machine learning can …
A brain tumor identification and classification using deep learning based on CNN-LSTM method
R Vankdothu, MA Hameed, H Fatima - Computers and Electrical …, 2022 - Elsevier
Brain tumors are one of the most often diagnosed malignant tumors in persons of all ages.
Recognizing its grade is challenging for radiologists in health monitoring and automated …
Recognizing its grade is challenging for radiologists in health monitoring and automated …