Pixel Normalization from Numeric Data as Input to Neural Networks
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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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2017.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.
- 2024ViTaL: An Advanced Framework for Automated Plant Disease Identification in Leaf Images Using Vision Transformers and Linear Projection For Feature Reductioncited by 2
- 2025Chaos into Order: Neural Framework for Expected Value Estimation of Stochastic Partial Differential Equationscited by 1
- 2023MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosiscited by 0
- 2025Chaos into Order: Neural Framework for Expected Value Estimation of Stochastic Partial Differential Equations5 Feb 2025
- 2024ViTaL: An Advanced Framework for Automated Plant Disease Identification in Leaf Images Using Vision Transformers and Linear Projection For Feature Reduction27 Feb 2024
- 2023MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosis25 Apr 2023