# Pixel Normalization from Numeric Data as Input to Neural Networks

arXiv: https://arxiv.org/abs/1705.01809 · HTML: https://mlsanity.com/paper/1705.01809/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 May 2017.

## Built on by (most cited first, 3 of 3)

- [ViTaL: An Advanced Framework for Automated Plant Disease Identification in Leaf Images Using Vision Transformers and Linear Projection For Feature Reduction](https://mlsanity.com/paper/2402.17424/) (2024)
- [Chaos into Order: Neural Framework for Expected Value Estimation of Stochastic Partial Differential Equations](https://mlsanity.com/paper/2502.03670/) (2025)
- [MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosis](https://mlsanity.com/paper/2304.13135/) (2023)

## Abstract (arXiv)

Text to image transformation for input to neural networks requires intermediate steps. This paper attempts to present a new approach to pixel normalization so as to convert textual data into image, suitable as input for neural networks. This method can be further improved by its Graphics Processing Unit (GPU) implementation to provide significant speedup in computational time.