论文标题
第一届农业视频挑战：方法和结果
The 1st Agriculture-Vision Challenge: Methods and Results
论文作者
论文摘要
第一个农业视频挑战旨在鼓励研究从空中图像中开发新颖和有效的农业模式识别算法，尤其是对于与我们的挑战数据集相关的语义细分任务。来自各个国家的大约57支参与的团队竞争，以实现空中农业语义细分的最先进。采用了农业视频挑战数据集，其中包括21,061台空中和多光谱的农田图像。本文提供了著名方法的摘要，并导致了挑战。我们的提交服务器和排行榜将继续为对此挑战数据集和任务感兴趣的研究人员开放；该链接可以在这里找到。
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially for the semantic segmentation task associated with our challenge dataset. Around 57 participating teams from various countries compete to achieve state-of-the-art in aerial agriculture semantic segmentation. The Agriculture-Vision Challenge Dataset was employed, which comprises of 21,061 aerial and multi-spectral farmland images. This paper provides a summary of notable methods and results in the challenge. Our submission server and leaderboard will continue to open for researchers that are interested in this challenge dataset and task; the link can be found here.
