期刊论文

Mango double-sided maturity online detection and classification system

中文

农业工程学报

1002-6819

2019

35

10

259-266

10.11975/j.issn.1002-6819.2019.10.033

湖南省重点研发计划（2017NK2131）；

本校为第一机构

芒果属于后熟水果,芒果成熟度分级可为芒果后熟、加工、包装、运输等工作提供便利条件。针对芒果形状不规则,难以对整个外观进行检测的问题,该文提出了一种基于迁移学习的芒果双面成熟度在线检测分级系统。通过上、下层输送带将芒果运输到图像采集区域,分别获取正、反面图像;2层输送带之间利用柔性翻面机构实现芒果无损翻面,通过压缩试验及ANSYS软件建模分析芒果承受挤压力范围。合并正、反2张图像并进行预处理,将数据以8:1.5:1.5的比例拆分为训练集、验证集、测试集,并用迁移学习方法在卷积神经网络模型进行芒果成熟度分级。使用卷积神经网络模型对芒果成熟度分级平均准确率达到96.72%,系统测定...

Mangoes are ripe fruits. The maturity classification of mangoes can provide convenience for mango ripening, processing, packaging and transportation. Compared with spherical fruit, mango is special shape and soft texture, and its multi-side images are difficult to acquire. Aiming at the irregular shape of mango and the difficulty of detecting the entire appearance, a mango double-sided maturity online detection and classification system based on transfer learning was proposed. The system is mainly composed of conveying device, flexible turning-...