# Exploring the Potential of VGG-16 Architecture for Accurate Brain Tumor Detection Using Deep Learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/exploring-the-potential-of-vgg-16-architecture-for-accurate-brain-tumor/

## Facts

| Field | Value |
| --- | --- |
| Author Names | P. Gayathri,Aiswarya V. L. S. Dhavileswarapu,Sufyan Ibrahim,Rahul Paul,Reena Gupta |
| Citations | 54 |
| DOI | 10.57159/gadl.jcmm.2.2.23056 |
| Fields | Computer Science,Medicine,Neuroscience |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://jcmm.co.in/index.php/jcmm/article/download/56/40 |
| OpenAlex ID | https://openalex.org/W4379519357 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Reena Gupta](https://scholariq.org/researchers/reena-gupta/)

## Paper journal

- [Journal of Computers Mechanical and Management](https://scholariq.org/journals/journal-of-computers-mechanical-and-management/)

## 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/)
- [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.