Overview
Who this competition fits
Builders comfortable with Chinese algorithm-competition pages hosted by iFlytek.
Read the original official blurb
农作物病害严重制约着农业生产，农作物生长过程中的各种病害会显著降低农产品的数量和质量，为了提高农业生产效率，及时发现和早期预防农作物病害对提高产量至关重要。图像处理和机器视觉能够适应复杂多变的自然场景，为苹果病害的识别和诊断奠定基础。利用计算机视觉和图像处理策略设计的苹果叶片病害智能识别算法，可以快速、低成本和精确地对农作物病害进行诊断和识别，有助于建… Official track: 计算机视觉. Sponsor: 北京林业大学. Teams entered: 597.
Preparation
From registration to a first submission
- 01
Can read Chinese competition pages
- 02
Comfortable submitting a baseline
- 03
Basic computer-vision experience
Before you commit: Task details, eligibility, and scoring rules live mainly on the official iFlytek page and change each season.
Source
How this page was assembled
Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.
- Official competition page
- iFlytek Challenge
- Last checked
- Apr 20, 2023