… methods is to use Deep Neural Network (DNN). In this paper, a Convolutional Neural Network
(CNN) has been used to detect a tumor through brain Magnetic Resonance Imaging (MRI) …

… in human brain. In this study, a deep learning-based method that uses different modalities
of MRI is presented for the segmentation of brain tumor. The proposed hybrid convolutional …

… This is because of a novel fused CNN model presented in this work for brain tumor
diagnosis accurately. The summary of existing deep learning methods is mentioned in Table 1. …

… ) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some
… reviewed to use deep learning techniques to produce a model for brain tumor detection. The …

… To detect brain tumor detection there exist different classical approaches but the present …
traditional neural network approach for detecting brain tumor, since the brain tumor detection …

… It is fully connected with one neuron with sigmoid activation as we have binary problem of
detecting brain tumor detection. If dense output is 1 then it indicates tumorous MRI. If dense …

… In this paper, we propose a system for automatically classifying brain tumors based on
two deep learning models. A “Fine-tuned proposed model with the attachment of the transfer …

… detection of MRI images using deep learning, classification of brain tumor from MRI images
using deep learning, detection and classification of brain tumor using deep learning etc. A …

… of diagnostic machine learning applications and predictive treatment. We plan … detect brain
tumour with neutrosophical principles in the future using the Convolutional Neural Network…

… This article proposes a new machine learning (ML) model to overcome this precise
segmentation of brain tumors. The proposed intelligent detection model for identifying brain tumors …