# Performance Analysis of Deep CNN, YOLO, and LeNet for Handwritten Digit Classification

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/performance-analysis-of-deep-cnn-yolo-and-lenet-for-handwritten-digit/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jibok Sarmah,Madan Lal Saini,Ankush Kumar,Vidhan Chasta |
| Citations | 16 |
| DOI | 10.1007/978-981-99-8479-4_16 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4390506683 |
| Type | conference-paper |
| Year | 2024 |

## Paper authors

- [Madan Lal Saini](https://scholariq.org/researchers/madan-lal-saini/)

## Paper primary topic

- [Handwritten Text Recognition Techniques](https://scholariq.org/topics/handwritten-text-recognition-techniques/)

## Paper topics

- [Handwritten Text Recognition Techniques](https://scholariq.org/topics/handwritten-text-recognition-techniques/)
- [Vehicle License Plate Recognition](https://scholariq.org/topics/vehicle-license-plate-recognition/)
- [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.