CattleNet-XAI: An explainable CNN framework for efficient cattle weight estimation.

ABSTRACT: 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 computer vision have facilitated the automation of weight prediction from image data. However, traditional regression models, such as Random Forest and Linear Regression, face challenges in capturing the complex, nonlinear relationships within image data, leading to less accurate predictions. To address these issues, we introduce CattleNet-XAI, a framework designed for both efficiency and explainability, which utilizes a custom Convolutional Neural Network (CNN). For the CNN-based approach, we incorporated advanced image

SUBMITTER: Hossain MJ 

PROVIDER: S-EPMC12614548 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature