# Multi-class classification of brain tumour magnetic resonance images using multi-branch network with inception block and five-fold cross validation deep learning framework

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/multi-class-classification-of-brain-tumour-magnetic-resonance-images-using-multi/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Deependra Rastogi,Prashant Johri,Varun Tiwari,Ahmed A. Elngar |
| Citations | 144 |
| DOI | 10.1016/j.bspc.2023.105602 |
| Fields | Computer Science,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4387802410 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Prashant Johri](https://scholariq.org/researchers/prashant-johri/)

## Paper primary topic

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

## Paper topics

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [Machine Learning and ELM](https://scholariq.org/topics/machine-learning-and-elm/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.