{"id":"W2802368751","doi":"10.1109/wacv.2018.00200","title":"ByLabel: A Boundary Based Semi-Automatic Image Annotation Tool","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Annotation; Boundary (topology); Computer science; Pixel; Automatic image annotation; Artificial intelligence; Image (mathematics); Computer vision; Enhanced Data Rates for GSM Evolution; Pattern recognition (psychology); Image retrieval; Mathematics","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":[0.002144638,0.001947334,0.001770569,0.005236241,0.001285798,0.002582604,0.004601397,0.002541194,0.01862649],"category_scores_gemma":[0.006795536,0.001260174,0.001331413,0.001684626,0.000888173,0.003669767,0.003667606,0.00132849,0.01276567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008304838,"about_ca_system_score_gemma":0.001341144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002164484,"about_ca_topic_score_gemma":0.003476651,"domain_scores_codex":[0.9971155,0.0005518646,0.0001720424,0.0006904228,0.001273494,0.0001966741],"domain_scores_gemma":[0.9946903,0.002123736,0.0003646199,0.001199531,0.001384696,0.0002371627],"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":[0.0007598922,0.0001823265,0.0009562271,0.001417306,0.00009663857,0.0003845564,0.0005035511,0.004905121,0.1080098,0.006348378,0.1096994,0.7667369],"study_design_scores_gemma":[0.0003989954,0.0004940508,0.003828576,0.0005180273,0.000117932,0.002957399,0.0007706719,0.4065832,0.2805334,0.02745513,0.2759254,0.0004171982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004320178,0.00044736,0.9095947,0.0001196073,0.0001394797,0.0002980851,0.001598788,0.07973374,0.003748024],"genre_scores_gemma":[0.03257388,0.0002323352,0.9496059,0.0002356267,0.00006114101,0.0006190701,0.005900421,0.006775691,0.003995849],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01862649,"threshold_uncertainty_score":0.06231177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103989858693329,"score_gpt":0.2896160727128892,"score_spread":0.2785761741259559,"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."}}