期刊论文

Yang, L

英文

Processes

2227-9717

2024

12

4

799-

10.3390/pr12040799

L.Y.: conceptualization, resources, supervision, project administration, and funding acquisition. B.C.: conceptualization, methodology, software, formal analysis, investigation, and writing—original draft. J.W.: software and validation. X.X.: software and validation. Y.L.: software and validation. Q.P.: methodology. Y.Z.: formal analysis and writing—review and editing. All authors have read and agreed to the published version of the manuscript. This study is mainly funded by the Science and technology research project of Hubei Grain Bureau (2023HBLSKJ005), the Youth Project of the Natural Science Foundation of Hubei Province (No. 2022CFB944), the Science and Technology Research Project of the Hubei Provincial Education Department (No. Q20211609), the Hubei Provincial grain bureau project (2023HBLSKJ004), and the Key R&D plan of Hubei Province (No. 2022BBA0047). Part of this research is supported by Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology (FM-202103) and the Science Foundation of Wuhan Polytechnic University (No. 2019RZ08, 2020J06).

本校为第一且通讯机构

With the development of machine vision technology, deep learning and image recognition technology has become a research focus for agricultural product non-destructive inspection. During the ripening process, banana appearance and nutrients clearly change, causing damage and unjustified economic loss. A high-efficiency banana ripeness recognition model was proposed based on a convolutional neural network and transfer learning. Banana photos at different ripening stages were collected as a dataset, and data augmentation was applied. Then, weights...