{"id":"W54451214","doi":"10.1007/978-3-642-15352-5_8","title":"Image Segmentation According to the Movement of Real Objects","year":2010,"lang":"en","type":"book-chapter","venue":"Springer topics in signal processing","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Segmentation; Artificial intelligence; Computer vision; Scale-space segmentation; Optical flow; Image segmentation; Segmentation-based object categorization; Parametric statistics; Pixel; Minimum spanning tree-based segmentation; Range segmentation; Computer science; Boundary (topology); Parametric model; Flow (mathematics); Pattern recognition (psychology); Mathematics; Image (mathematics); Geometry; Mathematical analysis; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004828545,0.0006471176,0.0007758766,0.001337074,0.0003843109,0.001445177,0.001031932,0.0009596933,0.005209568],"category_scores_gemma":[0.001094567,0.0006128522,0.0007000797,0.001830427,0.001210823,0.001349294,0.0005589611,0.000873878,0.00201218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006116853,"about_ca_system_score_gemma":0.0005235057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001051776,"about_ca_topic_score_gemma":0.001174595,"domain_scores_codex":[0.9996762,0.00003667663,0.0000168222,0.0001371161,0.0001002401,0.00003293109],"domain_scores_gemma":[0.9996934,0.0001250166,0.00003636466,0.00006258964,0.00005965849,0.00002298459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000583895,0.00004840062,0.0009687023,0.0008275957,0.00009668578,0.0003134744,0.0005386087,0.0337973,0.3495055,0.07233075,0.008263729,0.5327254],"study_design_scores_gemma":[0.00009468166,0.0003968227,0.008711939,0.0002313311,0.0002149607,0.001944597,0.0002699201,0.5845566,0.2173266,0.09772681,0.08841063,0.0001150648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.017482,0.00255625,0.9712206,0.0003161514,0.000342169,0.00008545288,0.0001687837,0.00107877,0.006749863],"genre_scores_gemma":[0.145,0.004877201,0.827885,0.0002055815,0.0003945506,0.0001238207,0.0007189678,0.0009284962,0.01986646],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005209568,"threshold_uncertainty_score":0.01742774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224641100876651,"score_gpt":0.2951203099852379,"score_spread":0.2728738989764714,"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."}}