Image processing steps applied in our research.

<div><p>Accurate estimation of cattle weight is essential for effective farm management, health assessment, and productivity optimization. Traditional manual methods for weight estimation, however, are labor-intensive, time-consuming, and prone to inaccuracies. Recent advances in compute...

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Bibliographic Details
Main Author:	Md Junayed Hossain (22615268) (author)
Other Authors:	Jannatul Ferdaus (22140270) (author), Ashraful Islam (1283403) (author), M. Ashraful Amin (22615271) (author)
Published:	2025
Subjects:	Sociology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified precise feature extraction mean absolute error less accurate predictions error case analysis demonstrates superior accuracy input data quality effective farm management pretrained efficientnetb3 model model significantly surpasses traditional manual methods associated weight data livestock weight estimation explainable cnn framework traditional regression models traditional methods weight estimation image data linear regression framework designed effective approach weight prediction cattle weight yolov5 algorithm study emphasizes results show recent advances random forest provide insights productivity optimization one variation mse ), making process low mae including normalization histogram equalization health assessment first leveraged face challenges especially cnn deep learning custom cnn conventional models computer vision cnn models cnn ). cattle images based approach 85 kg 02 kg
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Image processing steps applied in our research.

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