论文标题
车辆驾驶助手
Vehicle Driving Assistant
论文作者
论文摘要
在我们日常生活中，自动驾驶汽车一直是SAE 3级的汽车制造商（例如Tesla Spient Cars）的普遍术语。尽管这些车辆具有许多功能，例如停车援助和巡航控制，但它们主要是针对外国道路量身定制的。坑洼以及它们的丰富性是我们印度道路所独有的。我们认为，可以在各种场景中成功检测到视觉图像中的坑洼。此外，坑洼的颜色，形状和大小的多样性使这个问题成为使用现代机器学习和图像处理技术解决的恰当候选人。
Autonomous vehicles has been a common term in our day to day life with car manufacturers like Tesla shipping cars that are SAE Level 3. While these vehicles include a slew of features such as parking assistance and cruise control,they have mostly been tailored to foreign roads. Potholes, and the abundance of them, is something that is unique to our Indian roads. We believe that successful detection of potholes from visual images can be applied in a variety of scenarios. Moreover, the sheer variety in the color, shape and size of potholes makes this problem an apt candidate to be solved using modern machine learning and image processing techniques.
