# An efficient convolutional global gated recurrent-based adaptive gazelle algorithm for enhanced disease detection and classification

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/an-efficient-convolutional-global-gated-recurrent-based-adaptive-gazelle/

## Facts

| Field | Value |
| --- | --- |
| Author Names | S. P. Maniraj,Prameeladevi Chillakuru,Kavitha Thangavel,Archana Kadam,Sangeetha Meckanzi,Sreevardhan Cheerla |
| Citations | 1 |
| DOI | 10.1007/s12530-024-09598-1 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4399686719 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Prameeladevi Chillakuru](https://scholariq.org/researchers/prameeladevi-chillakuru/)

## Paper primary topic

- [Image Retrieval and Classification Techniques](https://scholariq.org/topics/image-retrieval-and-classification-techniques/)

## Paper topics

- [Image Retrieval and Classification Techniques](https://scholariq.org/topics/image-retrieval-and-classification-techniques/)
- [Advanced Image and Video Retrieval Techniques](https://scholariq.org/topics/advanced-image-and-video-retrieval-techniques/)
- [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.