Fruit Image Classification Based on MobileNetV2 with Transfer Learning Technique-Reference-Cited by-同舟云学术

Fruit Image Classification Based on MobileNetV2 with Transfer Learning Technique

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Conference on Computer Science and Application Engineering - CSAE 2019
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Author:

Xiang Qian¹,Wang Xiaodan¹,Li Rui¹,Zhang Guoling¹,Lai Jie¹,Hu Qingshuang¹

Affiliation:

1. College of Air and Missile Defense, Air Force Engineering University, Xi'an, China

Funder

National Natural Science Foundation of China

Publisher

ACM Press

Reference35 articles.

1. Zhang Jie, Li Yan-wen (2010). Research situation, problems and solutions of fruit-vegetable picking robots. Journal of Mechanical Design, 27(6), 1--5.

2. Liu, D., Shen, J., Yang, H., Niu, Q., & Guo, Q (2019). Recognition and localization of actinidia arguta based on image recognition. EURASIP Journal on Image and Video Processing, 2019(1), 21.

3. Feng, J., Zeng, L., & He, L (2019). Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis. Sensors, 19(4), 949. doi:10.3390/s19040949

4. Lin, G., Tang, Y., Zou, X., Xiong, J., & Fang, Y. (2019). Color-, depth-, and shape-based 3d fruit detection. Precision Agriculture.

5. Krizhevsky, A., Sutskever, I., & Hinton, G. (2012). ImageNet Classification with Deep Convolutional Neural Networks. NIPS(Vol.25). Curran Associates Inc.

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