{"id":"W4409603790","doi":"10.61091/jcmcc127b-244","title":"Image Style Conversion Optimization Method in Animation Design Based on Deep Convolutional Neural Networks","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Digital Media and Visual Art","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Animation; Artificial intelligence; Style (visual arts); Image (mathematics); Computer vision; Pattern recognition (psychology); Computer graphics (images); Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005407584,0.0007765412,0.0005334744,0.0007617605,0.0002118902,0.0006882692,0.0007689341,0.0005009675,0.001975453],"category_scores_gemma":[0.0008476821,0.0003059025,0.0007522166,0.0005519552,0.000316347,0.0008218623,0.0004467798,0.0009124107,0.0005477392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005647418,"about_ca_system_score_gemma":0.0004243236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002039726,"about_ca_topic_score_gemma":0.003066312,"domain_scores_codex":[0.9997122,0.00004276492,0.00001461995,0.0000818346,0.0001133949,0.00003520374],"domain_scores_gemma":[0.9998056,0.00004324612,0.00002432205,0.00004242439,0.00006819524,0.00001623536],"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":[0.0001556799,0.00009214741,0.00178501,0.0001411468,0.0001086271,0.00009264526,0.00007906396,0.3137796,0.04215796,0.006679922,0.004380988,0.6305472],"study_design_scores_gemma":[0.000008785038,0.00003347288,0.0003344275,0.000006436459,0.0000161112,0.00005085833,0.000007889862,0.9879175,0.008590451,0.001571991,0.00145538,0.000006759209],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02918287,0.0004862006,0.9654205,0.0001417783,0.00009193744,0.00005491134,0.00007723767,0.00129343,0.003251245],"genre_scores_gemma":[0.5472907,0.0007473797,0.4390565,0.0003815488,0.00009721605,0.0001054011,0.0005243325,0.0004037306,0.01139331],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002039726,"threshold_uncertainty_score":0.006608546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01499926076348392,"score_gpt":0.2786071193623202,"score_spread":0.2636078585988363,"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."}}