# Lensless-camera based machine learning for image classification

arXiv: https://arxiv.org/abs/1709.00408 · HTML: https://mlsanity.com/paper/1709.00408/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Sep 2017.

## Built on by (most cited first, 2 of 2)

- [Text detection and recognition based on a lensless imaging system](https://mlsanity.com/paper/2210.04244/) (2022)
- [Hand Gestures Recognition in Videos Taken with Lensless Camera](https://mlsanity.com/paper/2210.08233/) (2022)

## Abstract (arXiv)

Machine learning (ML) has been widely applied to image classification. Here, we extend this application to data generated by a camera comprised of only a standard CMOS image sensor with no lens. We first created a database of lensless images of handwritten digits. Then, we trained a ML algorithm on this dataset. Finally, we demonstrated that the trained ML algorithm is able to classify the digits with accuracy as high as 99% for 2 digits. Our approach clearly demonstrates the potential for non-human cameras in machine-based decision-making scenarios.