{"id":"W3035665735","doi":"10.1007/s10462-020-09854-1","title":"Deep semantic segmentation of natural and medical images: a review","year":2020,"lang":"en","type":"review","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":849,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal; Simon Fraser University","funders":"","keywords":"Computer science; Artificial intelligence; Segmentation; Image segmentation; Categorization; Context (archaeology); Task (project management); Image (mathematics); Segmentation-based object categorization; Deep learning; Pattern recognition (psychology); Scale-space segmentation; Computer vision; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137390998662466,"score_gpt":0.3068003099155884,"score_spread":0.2954263999289637,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}