Brain tumor MRI classification on Figshare
98.95AccuracyAgglomerative clustering with softmax
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| Agglomerative clustering with softmaxFeatures extracted=Feature vectors—combined to form a hybrid feature vector using the partial least squares (PLS)2025.02 | 98.95 | — | — | — | — | |
| SAETCNTypes of Classifier=SAETCN - Self-Attention Enhancement Tumor Classification Network, Year of Publish=20242025.12 | 98.69 | — | — | — | — | |
| Badza et al.Types of Classifier=22 layers CNN, Year of Publish=20202025.12 | 96.56 | — | — | — | — | |
| Convolutional neural network based on complex networks (CNNBCN)Features extracted=Modified activation function2025.02 | 95.49 | — | — | — | — | |
| Sai Samarth R. Phaye et al.Types of Classifier=DCNet++, Year of Publish=20182025.12 | 95.03 | — | — | — | — | |
| Pashaei et al.Types of Classifier=CNN, Year of Publish=20182025.12 | 93.68 | — | — | — | — | |
| Sai Samarth R. Phaye et al.Types of Classifier=DCNet, Year of Publish=20182025.12 | 93.04 | — | — | — | — | |
| Paul et al.Types of Classifier=CNN, Year of Publish=20172025.12 | 91.43 | — | — | — | — | |
| Abiwinanda et al.Types of Classifier=CNN, Year of Publish=20182025.12 | 84.19 | — | — | — | — |