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All issues Volume 448 (2023) E3S Web Conf., 448 (2023) 02059 References
Open Access
Issue
E3S Web Conf.
Volume 448, 2023
The 8th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2023)
Article Number 02059
Number of page(s) 11
Section Information System
DOI https://doi.org/10.1051/e3sconf/202344802059
Published online 17 November 2023
  1. K. Adi, S. Pujiyanto, O. D. Nurhayati, dan A. Pamungkas, Beef quality identification using color analysis and k-nearest neighbor classification, in 2015 4th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME), 180–184 (2015) [Google Scholar]
  2. E. Nematinia dan S. Abdanan Mehdizadeh, Assessment of egg freshness by prediction of Haugh unit and albumen pH using an artificial neural network, J. Food Meas. Charact., 12, 3, 1449–1459 (2018) [Google Scholar]
  3. F. G. Santeramo dkk., Emerging trends in European food, diets and food industry, Food Res. Int., 104, October 2017, 39–47 (2018) [CrossRef] [Google Scholar]
  4. A. Nasiri, M. Omid, dan A. Taheri-garavand, An automatic sorting system for unwashed eggs using deep learning, J. Food Eng., 283, February, 110036 (2020) [Google Scholar]
  5. M. Turkoglu, Defective egg detection based on deep features and Bidirectional, Comput. Electron. Agric., 185, May 2020, 106152 (2021) [CrossRef] [Google Scholar]
  6. L. Wu, Q. Wang, D. Jie, S. Wang, Z. Zhu, dan L. Xiong, Detection of crack eggs by image processing and soft-margin support vector machine, J. Comput. Methods Sci. Eng., 18, 21–31 (2018) [Google Scholar]
  7. V. Moysiadis, P. Sarigiannidis, V. Vitsas, dan A. Khelifi, Smart Farming in Europe, Comput. Sci. Rev., 39, 100345, Feb (2021) [CrossRef] [Google Scholar]
  8. G. Idoje, T. Dagiuklas, dan M. Iqbal, Survey for smart farming technologies : Challenges and issues ✩, Comput. Electr. Eng., 92, February 2020, 107104 (2021) [CrossRef] [Google Scholar]
  9. Y. M. Valencia dkk., A novel method for inspection defects in commercial eggs using computer vision, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. - ISPRS Arch., 43, B2-2021, 809–816 (2021) [CrossRef] [Google Scholar]
  10. K. Adi, S. Pujiyanto, O. Dwi Nurhayati, dan A. Pamungkas, Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone, J. Food Qual., 2017, 1674718 (2017) [Google Scholar]
  11. O. Russakovsky dkk., ImageNet Large Scale Visual Recognition Challenge, Int. J. Comput. Vis., 115, 3, 211–252 (2015) [Google Scholar]
  12. K. Adi, C. E. Widodo, A. P. Widodo, R. Gernowo, A. Pamungkas, dan R. A. Syifa, Detection Lung Cancer Using Gray Level Co-Occurrence Matrix (GLCM) and Back Propagation Neural Network Classification, J. Eng. Sci. Technol. Rev., 11, 6, 7–13 (2018) [CrossRef] [Google Scholar]
  13. X. Deng, Q. Wang, H. Chen, dan H. Xie, Eggshell crack detection using a wavelet-based support vector machine, Comput. Electron. Agric., 70, 1, 135–143 (2010) [CrossRef] [Google Scholar]
  14. B. Guanjun, J. Mimi, X. Yi, C. Shibo, dan Y. Qinghua, Cracked egg recognition based on machine vision, Comput. Electron. Agric., 158, January, 159–166 (2019) [CrossRef] [Google Scholar]
  15. R. G. Coutiño, Defect detection in eggshell using a vision system to ensure the incubation in poultry production, Measurement, 135, 39–46 (2019) [CrossRef] [Google Scholar]
  16. Y. LeCun, Y. Bengio, dan G. Hinton, Deep learning, Nature, 521, 7553, 436–444 (2015) [CrossRef] [PubMed] [Google Scholar]
  17. K. Adi, C. E. Widodo, A. P. Widodo, dan U. S. Margiati, Detection of Foreign Object Debris (Fod) Using Convolutional Neural Network (Cnn), J. Theor. Appl. Inf. Technol., 100, 1, 184–191 (2022) [Google Scholar]
  18. Y. Liu, H. Pu, dan D. Sun, Trends in Food Science & Technology Efficient extraction of deep image features using convolutional neural network ( CNN ) for applications in detecting and analysing complex food matrices, Trends Food Sci. Technol., 113, May, 193–204 (2021) [CrossRef] [Google Scholar]
  19. B. Botta, S. S. R. Gattam, dan A. K. Datta, Eggshell crack detection using deep convolutional neural networks, J. Food Eng., 315, May 2021, 110798 (2022) [Google Scholar]
  20. Y. Tian, Artificial Intelligence Image Recognition Method Based on Convolutional Neural Network Algorithm, IEEE Access, 8, 125731–125744 (2020) [CrossRef] [Google Scholar]
  21. SNI 01-3926:2008, SNI 3926:2008 Telur Ayam Konsumsi, Standar Nas. Indones., 1–8 (2008) [Google Scholar]

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