基于深度学习的小浆果一体化智能采摘与分选研究进展

小浆果因具有较高的营养价值和保健作用深受人们喜爱，被国际市场誉为第3代水果。随着市场需求量的增加，林业小浆果的智能采摘与分选成为一种新的趋势。目前，由于现有技术自动化和智能化程度不高，导致大量人力、物力的投入。深度学习方法的飞速发展促进了检测技术的精确作业和检测精度的提高。文中概述了深度学习的发展进程，通过总结国内外关于深度学习方法在小浆果采摘与分选中的应用，提出深度学习方法在实际应用过程中存在的问题及解决措施，并展望深度学习方法在小浆果智能采摘与分选检测方面的发展趋势。

Research Progress on Integrated Intelligent Picking and Sorting of Small Berries Based on Deep Learning

Small berries are the favorite fruit of people as the third generation fruit known in the international market, due to the high nutrition and healthcare function. As the market demand increases, the intelligent picking and sorting for small berries become a new trend. At present, the commonly used technologies have the low degree of automation and intelligence, resulting in more human and material input, while the rapid development of the deep learning technology improves the accuracy and precision for detection technology. The paper reviews the development process of deep learning, summarizes the applications of deep learning to small berry picking and sorting, and identifies the problems and resolutions for the practical applications of deep learning. Finally, the development trend of intelligent picking and sorting detection for small berry is prospected by using deep learning.