实验科学与技术2025，Vol.23Issue(4)：20-24,5.DOI:10.12179/1672-4550.20240100
基于多尺度卷积神经网络的草莓畸变识别实验设计
Experimental Design of Strawberry Distortion Recognition Based on the Multi-Scale Convolutional Neural Network
摘要
Abstract
In order to cultivate students'ability of development and application practice,an experimental case for strawberry distortion recognition based on multi-scale convolutional neural networks is designed,according to the curriculum experiment setup,to facilitate students'learning and hands-on practice.An algorithm for recognizing distorted strawberry images is implemented using multi-scale convolutional neural network to improve the recognition capability for distorted strawberry images.The experimental results show that the algorithm possesses accurate recognition ability for distorted strawberry images and effectively reduces the impact of factors such as illumination and background.Through this experimental case,students'understanding of artificial intelligence knowledge is deepened,their interest in learning artificial intelligence is cultivated,and their ability to develop and apply artificial intelligence projects is improved.关键词
人工智能导论/电子信息工程专业/卷积神经网络/实验案例Key words
introduction to artificial intelligence/electronic and information engineering/convolutional neural network/experimental case分类
信息技术与安全科学引用本文复制引用
闫静杰,李培原,周晓阳,丁俊丰,王晨昱,卢官明..基于多尺度卷积神经网络的草莓畸变识别实验设计[J].实验科学与技术,2025,23(4):20-24,5.基金项目
南京邮电大学教学改革招标项目(JG00218JX01) （JG00218JX01）
南京邮电大学教学改革项目(2022XSG03) （2022XSG03）
国家自然科学基金面上项目(61971236). （61971236）
