# E-TLCNN Classification using DenseNet on Various Features of Hypertensive Retinopathy (HR) for Predicting the Accuracy

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/e-tlcnn-classification-using-densenet-on-various-features-of-hypertensive/

## Facts

| Field | Value |
| --- | --- |
| Author Names | N. Deepa,T Devi. |
| Citations | 22 |
| DOI | 10.1109/iciccs51141.2021.9432255 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3169011232 |
| Type | conference-paper |
| Year | 2021 |

## Paper authors

- [T Devi.](https://scholariq.org/researchers/t-devi/)

## Paper primary topic

- [Retinal Imaging and Analysis](https://scholariq.org/topics/retinal-imaging-and-analysis/)

## Paper topics

- [Retinal Imaging and Analysis](https://scholariq.org/topics/retinal-imaging-and-analysis/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)
- [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.