{"id":"W4387572923","doi":"10.3390/app132011189","title":"A Review of Image Inpainting Methods Based on Deep Learning","year":2023,"lang":"en","type":"review","venue":"Applied Sciences","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Inpainting; Artificial intelligence; Computer science; Deep learning; Image (mathematics); Computer vision; Field (mathematics); Feature (linguistics); Image restoration; Pattern recognition (psychology); Feature extraction; Image processing; 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":[0.0004328536,0.001002172,0.0008532432,0.002265428,0.0002420565,0.0007346467,0.0008936615,0.001003886,0.004678337],"category_scores_gemma":[0.001037264,0.0004598198,0.0006613381,0.002554902,0.0003278399,0.001412932,0.0004767649,0.001289648,0.00224612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004410999,"about_ca_system_score_gemma":0.0008021475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001145337,"about_ca_topic_score_gemma":0.001371156,"domain_scores_codex":[0.9998093,0.00002236005,0.00002675765,0.00004544359,0.00008207203,0.00001396867],"domain_scores_gemma":[0.9995085,0.0002738179,0.00004230183,0.00001990502,0.000134957,0.00002050141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003692858,0.00008110473,0.0002010722,0.01242066,0.00009184299,0.0001014167,0.00005884104,0.002625722,0.002427669,0.008588724,0.02588129,0.9474847],"study_design_scores_gemma":[0.0000153789,0.0001791517,0.0009941587,0.004246866,0.0002142344,0.001258138,0.00005589997,0.00474261,0.003181168,0.007830105,0.9772242,0.00005800627],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005762615,0.9812281,0.01153305,0.0004977418,0.0004358366,0.00002205703,0.00009169368,0.00009331083,0.005521915],"genre_scores_gemma":[0.004145906,0.9847518,0.006991067,0.000365651,0.0005248145,0.00002823729,0.000174972,0.00002526337,0.002992284],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004678337,"threshold_uncertainty_score":0.01565063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08770687798474226,"score_gpt":0.399027600227316,"score_spread":0.3113207222425737,"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."}}