{"id":"W4394597431","doi":"10.1109/csce60160.2023.00315","title":"Multi-Modality Image Inpainting Using Generative Adversarial Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inpainting; Adversarial system; Modality (human–computer interaction); Computer science; Artificial intelligence; Generative grammar; Image (mathematics); Computer vision; Generative adversarial network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007240301,0.0008657846,0.0006407761,0.0002991908,0.0001661221,0.0005924383,0.0008979124,0.0007854145,0.001779549],"category_scores_gemma":[0.001383107,0.0003942664,0.0007207855,0.0003265752,0.0007789225,0.0006975876,0.0009876437,0.001904151,0.000319836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005226621,"about_ca_system_score_gemma":0.0003115993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001173324,"about_ca_topic_score_gemma":0.001588833,"domain_scores_codex":[0.9997212,0.0000857672,0.000008397466,0.00007335561,0.00007976295,0.00003155659],"domain_scores_gemma":[0.9994767,0.0003231314,0.00005990437,0.00007292757,0.00004317306,0.00002414889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008555125,0.00004500386,0.0003551375,0.0001004548,0.00007087032,0.0001394129,0.00006980533,0.9188156,0.01513965,0.01070869,0.001843535,0.05262632],"study_design_scores_gemma":[0.000004417548,0.00001737946,0.00007382281,0.000005570586,0.00000676743,0.00004408473,0.000004287028,0.9932725,0.00225419,0.003750552,0.0005620698,0.000004276077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009765455,0.0003981872,0.9874342,0.000206954,0.00005028307,0.0000283485,0.00005513653,0.0004236965,0.001637752],"genre_scores_gemma":[0.7823129,0.001091711,0.208404,0.0004644632,0.0001388598,0.0001051745,0.0002928975,0.0002175067,0.006972309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001779549,"threshold_uncertainty_score":0.005953193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0424320420686888,"score_gpt":0.287423239727376,"score_spread":0.2449911976586872,"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."}}