Computer Applications and Software, Volume. 42, Issue 4, 174(2025)

NON-DESTRUCTIVE DETECTION OF EARLY FERTILIZATION INFORMATION OF CHICKEN EGGS BASED ON DEEP LEARNING

Liu Yangyang1, Cui Dejian1, Jia Weie1, Xia Yuantian1, Lian Zhengxing2, and Li Lin1
Author Affiliations
  • 1College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
  • 2College of Animal Science & Technology, China Agricultural University, Beijing 100094, China
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    References(4)

    [5] [5] Dong J, Dong X G, Li Y L, et al. Identification of unfertilized duck eggs before hatching using visible/near infrared transmittance spectroscopy[J]. Computers and Electronics in Agriculture, 2019, 157: 471-478.

    [7] [7] Ghaderi M, Banakar A, Masoudi A. Using dielectric properties and intelligent methods in separating of hatching eggs during incubation[J]. Measurement, 2018, 114: 191-194.

    [13] [13] Hashemzadeh M, Farajzadeh N. A machine vision system for detecting fertile eggs in the incubation industry[J]. International Journal of Computational Intelligence Systems, 2016, 9 (5): 850-862.

    [14] [14] Dong J, Lu B, He K, et al. Assessment of hatching properties for identifying multiple duck eggs on the hatching tray using machine vision technique[J]. Computers and Electronics in Agriculture, 2021, 184: 106076.

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    Liu Yangyang, Cui Dejian, Jia Weie, Xia Yuantian, Lian Zhengxing, Li Lin. NON-DESTRUCTIVE DETECTION OF EARLY FERTILIZATION INFORMATION OF CHICKEN EGGS BASED ON DEEP LEARNING[J]. Computer Applications and Software, 2025, 42(4): 174

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    Paper Information

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    Received: Dec. 7, 2021

    Accepted: Aug. 25, 2025

    Published Online: Aug. 25, 2025

    The Author Email:

    DOI:10.3969/j.issn.1000-386x.2025.04.026

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