# Deep Learning Advances in Brain Tumor Classification: Leveraging VGG16 and MobileNetV2 for Accurate MRI Diagnostics

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-advances-in-brain-tumor-classification-leveraging-vgg16-and/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Alex David S,Almas Begum,S. Ismail Kalilulah,Ruth Naveena N,K. Rajathi,D Hemalatha |
| Citations | 22 |
| DOI | 10.1109/icpects62210.2024.10780014 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4405304110 |
| Type | conference-paper |
| Year | 2024 |

## Paper authors

- [Alex David S](https://scholariq.org/researchers/alex-david-s/)
- [Almas Begum](https://scholariq.org/researchers/almas-begum/)
- [D Hemalatha](https://scholariq.org/researchers/d-hemalatha/)

## 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/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

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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.