{"id":"W3034512672","doi":"10.1109/cvpr42600.2020.00915","title":"PolyTransform: Deep Polygon Transformer for Instance Segmentation","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Segmentation; Polygon (computer graphics); Computer science; Artificial intelligence; Exploit; Image segmentation; Scale-space segmentation; Computer vision; Segmentation-based object categorization; Pattern recognition (psychology)","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":[0.0006067681,0.001783063,0.00144835,0.001437043,0.0005551496,0.002423875,0.003789353,0.001567016,0.01020448],"category_scores_gemma":[0.002328893,0.0008570118,0.001535132,0.001462409,0.0009741223,0.003759646,0.002023956,0.002777616,0.00570264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387463,"about_ca_system_score_gemma":0.001053606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004810666,"about_ca_topic_score_gemma":0.009938872,"domain_scores_codex":[0.9992856,0.00006387971,0.00002883552,0.0003227474,0.0002240285,0.00007483517],"domain_scores_gemma":[0.9994062,0.0001434011,0.00005289588,0.0002750267,0.00007338692,0.00004912954],"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":[0.0005923397,0.0002053651,0.001872827,0.000392115,0.0001842446,0.0004159409,0.0002093062,0.1620058,0.03241824,0.02914441,0.04277257,0.7297869],"study_design_scores_gemma":[0.00003576339,0.00006556013,0.0003505687,0.00002156773,0.0000229089,0.00025526,0.00005054493,0.9420083,0.02364048,0.01912886,0.01439517,0.00002504098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01244115,0.0003179659,0.9518968,0.0002116189,0.0001298535,0.0001443924,0.00152561,0.02959861,0.003733979],"genre_scores_gemma":[0.1740432,0.0004038621,0.8006685,0.0005184559,0.000106209,0.0001918937,0.01144344,0.004917146,0.007707212],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01020448,"threshold_uncertainty_score":0.03413731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02691956037334562,"score_gpt":0.2710345626970707,"score_spread":0.244115002323725,"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."}}