# Deep Transfer Learning Approaches in Performance Analysis of Brain Tumor Classification Using MRI Images

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-transfer-learning-approaches-in-performance-analysis-of-brain-tumor/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Chetana Srinivas,Nandini Prasad K. S.,Mohammed Zakariah,Yousef Ajmi Alothaibi,Kamran Shaukat,B. Partibane,Awal Halifa |
| Citations | 335 |
| DOI | 10.1155/2022/3264367 |
| Fields | Computer Science,Neuroscience |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://downloads.hindawi.com/journals/jhe/2022/3264367.pdf |
| OpenAlex ID | https://openalex.org/W4220879402 |
| PMID | 35299683 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Mohammed Zakariah](https://scholariq.org/researchers/mohammed-zakariah/)

## Paper journal

- [Journal of Healthcare Engineering](https://scholariq.org/journals/journal-of-healthcare-engineering/)

## 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/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Machine Learning and ELM](https://scholariq.org/topics/machine-learning-and-elm/)

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