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What is Health Assessment of Broiler Chickens about?

This study presents a deep learning framework utilizing thermal imaging to automate health assessments of broiler chickens, achieving a validation accuracy of 88%. The framework employs a lightweight MobileNetV2 architecture and incorporates techniques such as Contrast Limited Adaptive Histogram Equalization (CLAHE) for image enhancement and class weighting to address dataset imbalances. The findings indicate that automated thermal screening can effectively identify sick birds early, improving animal welfar

Author

okbye7910

Language

EN