MFTs-Net: A Deep Learning Approach for High Similarity Date Fruit Recognition-Reference-Cited by-同舟云学术

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MFTs-Net: A Deep Learning Approach for High Similarity Date Fruit Recognition

Published:2023 Issue:6 Volume:14 Page:1151-1158
ISSN:1798-2340
Container-title:Journal of Advances in Information Technology
language:
Short-container-title:JAIT

Author:

Zaar Abdellah El,Assawab Rachida,Aoulalay Ayoub,Benaya Nabil,Bakir Toufik,Femmam Smain,Allati Abderrahim El

Publisher

Engineering and Technology Publishing

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems,Software

Link

http://www.jait.us/uploadfile/2023/JAIT-V14N6-1151.pdf

Reference24 articles.

1. [1] P. Liu, W. Yuan, J. Fu, Z. Jiang, H. Hayashi, and G. Neubig, "Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing," ACM Computing Surveys, vol. 55, no. 9, pp. 1-35, 2023.

2. [2] Y. Bai, B. Zhang, N. Xu, J. Zhou, J. Shi, and Z. Diao, "Vision-based navigation and guidance for agricultural autonomous vehicles and robots: A review," Computers and Electronics in Agriculture, vol. 205, 107584, 2023.

3. [3] T. W. Cenggoro, B. Pardamean et al., "A systematic literature review of machine learning application in covid-19 medical image classification," Procedia Computer Science, vol. 216, pp. 749-756, 2023.

4. [4] R. P. Masini, M. C. Medeiros, and E. F. Mendes, "Machine learning advances for time series forecasting," Journal of Economic Surveys, vol. 37, no. 1, pp. 76-111, 2023.

5. [5] O. Liouane, S. Femmam, T. Bakir, and A. B. Abdelali, "Improved two hidden layers extreme learning machines for node localization in range free wireless sensor networks," J. Commun., vol. 16, no. 12, pp. 528-534, 2021.

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