技术
- 分析与建模 - 机器学习
适用行业
- 农业
- 教育
适用功能
- 质量保证
用例
- 计算机视觉
- 视觉质量检测
服务
- 测试与认证
- 培训
关于客户
Advanced.farm 是一家利用机器人技术自动完成农业中最艰巨任务的公司,致力于打造农业的未来,使农场更安全、更高效。他们专注于资源最密集的任务,并拥有草莓和苹果采摘的自动化解决方案。他们计划在不久的将来扩展到其他挑战。 Advanced.farm 正在通过结合先进的机器人技术、自主导航和最先进的计算机视觉机器学习 (CVML) 堆栈来构建先进的农业设备平台。
挑战
Advanced.farm 是一家专注于利用机器人技术实现农业任务自动化的公司,在提高其苹果采摘能力方面面临着挑战。苹果品种繁多,采摘季节短,很难跟上步伐。当他们为苹果开发计算机视觉机器学习 (CVML) 功能时,他们需要一个标签解决方案,使他们能够定期创建新项目并快速获得标签图像的周转。为了在第一个苹果采摘季节取得成功,他们必须通过注释管道快速处理大量图像,适应不断变化的苹果品种,并确保他们的模型在真实情况下尽可能准确和高效数据。
解决方案
为了应对这一挑战,Advanced.farm 开始与 Scale Rapid 合作获取大量高质量注释。这些注释提供了 Advanced.farm 改进其模型所需的数据。最初,他们使用 Scale Studio,利用他们的标签团队来利用他们的领域专业知识。然而,他们很快意识到,他们希望训练模型的数据集大小需要更多的工作,超出了内部员工的处理能力。为了管理从草莓到苹果以及规模到新果园的过渡,Advanced.farm 转向 Scale,通过准确标记的苹果可靠、稳健地生成训练数据。借助 Scale Rapid,他们能够在 24 小时内获得高质量数据,这有助于他们根据需求的变化在整个苹果季节进行迭代。 Advanced.farm 要求在 24 小时内返回 50,000 个注释,而 Scale 在该时间内高质量地完成了这些注释。
运营影响
数量效益
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