… in brain image classification … -classification of the brain tumors using publicly available
datasets. We have proposed a dense EfficientNet network for three-class brain tumor classification …

… brain tumor detection. In this research, a transfer learning-based fine-tuning approach for
the classification of brain tumors into three classes ie glioma, meningioma, and pituitary tumor …

… accuracy can be further be increased with an efficient framework. In this manuscript, an
efficient brain tumor classification model that can effectively classify tumors, ie, Meningioma, …

… By leveraging the strengths of EfficientNet models, we aim to develop a highly accurate
and efficient system for brain tumor classification, ultimately improving patient diagnosis and …

… In this study, we present two fast and proficient brain tumor … detection and classification of
different types of brain tumors. We … brain tumors as gliomas, meningiomas, or pituitary tumors. …

… In this study, a deep convolutional neural network (CNN) EfficientNet-B0 base model is
fine-tuned with our proposed layers to efficiently classify and detect brain tumor images. The …

… This paper presented an efficient deep learning-based framework for brain tumor classification.
The proposed framework gave four different weight initialization configurations in the …

… using a fine-grained classification approach. Furthermore, … defined tumor regions to detect
and classify brain tumors that … and efficient deep TL model for brain tumor classification. We …

… CNN-based systematic approach to diagnose brain tumors and evaluating its accuracy, …
patients with three classes of brain tumors and a class of normal brain obtained from Radiopedia …

… brain tumor classification methods using deep learning have also attracted widespread
attentions. In this work, we present a novel brain tumor classification … the most efficient models …