Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs.

ABSTRACT: The slaughterhouse can act as a valid checkpoint to estimate the prevalence and the economic impact of diseases in farm animals. At present, scoring lesions is a challenging and time-consuming activity, which is carried out by veterinarians serving the slaughter chain. Over recent years, artificial intelligence(AI) has gained traction in many fields of research, including livestock production. In particular, AI-based methods appear able to solve highly repetitive tasks and to consistently analyze large amounts of data, such as those collected by veterinarians during postmortem inspection in high-throughput slaughterhouses. The present study aims to develop an AI-based method capable of recognizing and quantifying enzootic pneumonia-like lesions on digital images captured from slaughtered p

SUBMITTER: Bonicelli L 

PROVIDER: S-EPMC8614402 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature