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Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology

2024/05/14 by Laura Gálvez Jiménez, Christine Decaestecker · 1 citation
Computer Science · #AI in cancer detection #Annotation #Artificial intelligence #Artificial neural network #Computer science #Context (archaeology) #Crowdsourcing #Digital Imaging for Blood Diseases #Digital pathology #Image (mathematics) #Machine Learning and Data Classification #Machine learning #Market segmentation #Noise (video) #Overfitting #Pattern recognition (psychology) #Process (computing) #Segmentation #Set (abstract data type) #Task (project management) #Training set

paper · doi:10.1016/j.compbiomed.2024.108586

openalex publication_date 2024/05/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

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