# DISHA: Low-Energy Sparse Transformer at Edge for Outdoor Navigation for the Visually Impaired Individuals

arXiv: https://arxiv.org/abs/2406.15864 · HTML: https://mlsanity.com/paper/2406.15864/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 21 references that are in the map.
- First posted on arXiv 22 Jun 2024.

## Builds on (most cited first, 6 of 6)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://mlsanity.com/paper/2105.15203/) (2021)
- [Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers](https://mlsanity.com/paper/2012.15840/) (2020)
- [Fast-SCNN: Fast Semantic Segmentation Network](https://mlsanity.com/paper/1902.04502/) (2019)
- [Smart Guiding Glasses for Visually Impaired People in Indoor Environment](https://mlsanity.com/paper/1709.09359/) (2017)
- [Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People](https://mlsanity.com/paper/1904.13037/) (2019)

## Built on by (most cited first, 1 of 1)

- [mmWalk: Towards Multi-modal Multi-view Walking Assistance](https://mlsanity.com/paper/2510.11520/) (2025)

## Abstract (arXiv)

Assistive technology for visually impaired individuals is extremely useful to make them independent of another human being in performing day-to-day chores and instill confidence in them. One of the important aspects of assistive technology is outdoor navigation for visually impaired people. While there exist several techniques for outdoor navigation in the literature, they are mainly limited to obstacle detection. However, navigating a visually impaired person through the sidewalk (while the person is walking outside) is important too. Moreover, the assistive technology should ensure low-energy operation to extend the battery life of the device. Therefore, in this work, we propose an end-to-end technology deployed on an edge device to assist visually impaired people. Specifically, we propose a novel pruning technique for transformer algorithm which detects sidewalk. The pruning technique ensures low latency of execution and low energy consumption when the pruned transformer algorithm is deployed on the edge device. Extensive experimental evaluation shows that our proposed technology provides up to 32.49% improvement in accuracy and 1.4 hours of extension in battery life with respect to a baseline technique.