EfficientNet and multi-path convolution with multi-head attention network for brain tumor grade classification

Classification of Brain Image Tumor using EfficientNet B1-B2 Deep Learning

“…Research conducted by (Tabatabaei et al, 2023) proposed a more compact and enhanced CNN architecture (iResNet) that will recognize tumor features from MR images CNN iVGG, iDensNet, and iResNet with the best results reaching 99.30% with the iResNet model. Research conducted by (Isunuri & Kakarla, 2023) For the grade classification, suggest an EfficientNet and multi-path convolution with a multi-head attention network. When extracting features, employed an EfficientNetB4 that had already been trained.…”

“…Research related to brain tumors using deep learning methods has attracted the interest of world researchers (Dang et al, 2022;Demir et al, 2023;Emam et al, 2023;Farajzadeh et al, 2023;Kanchanamala et al, 2023;Mehnatkesh et al, 2023;Tabatabaei et al, 2023). Previous research used the Convolutional Neural Networks (CNN) method with the EfficientNet architecture (Isunuri & Kakarla, 2023;Nayak et al, 2022;Shah et al, 2022;Tripathy et al, 2023;Zulfiqar et al, 2023), multi-class Support Vector Machine (SVM) and fuzzy classifier (Vankdothu & Hameed, 2022), hybrid model combined CNN and SVM (Khairandish et al, 2022), SVM and Artificial Neural Network (ANN) (Sachdeva et al, 2016), hybrid machine learning (ML) k-nearest https://journal.umy.ac.id/index.php/st/issue/view/1064 neighbour and k-means clustering (Rinesh et al, 2022), accelerated particle swarm optimization (APSO) based artificial neural network model (ANNM) (Pradeep et al, 2022), particle swarm optimization (PCA) algorithms (Zahid et al, 2022), atomic force microscopy (AFM) (Huml et al, 2023), CNN-pretrained ResNet-50, Inception-v3, and VGG-16 (Srinivas et al, 2022), Genetic Algorithm and U-Net (Arif et al, 2022).…”