# Applying Semantic Segmentation to Autonomous Cars in the Snowy Environment

arXiv: https://arxiv.org/abs/2007.12869 · HTML: https://mlsanity.com/paper/2007.12869/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jul 2020.

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

- [A workflow for segmenting soil and plant X-ray CT images with deep learning in Googles Colaboratory](https://mlsanity.com/paper/2203.09674/) (2022)

## Abstract (arXiv)

This paper mainly focuses on environment perception in snowy situations which forms the backbone of the autonomous driving technology. For the purpose, semantic segmentation is employed to classify the objects while the vehicle is driven autonomously. We train the Fully Convolutional Networks (FCN) on our own dataset and present the experimental results. Finally, the outcomes are analyzed to give a conclusion. It can be concluded that the database still needs to be optimized and a favorable algorithm should be proposed to get better results.