{"id":"W4389160135","doi":"10.1109/tip.2023.3335828","title":"KBStyle: Fast Style Transfer Using a 200 KB Network With Symmetric Knowledge Distillation","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Key Technology Research and Development Program of Shandong; National Natural Science Foundation of China","keywords":"Distillation; Computer science; Style (visual arts); Artificial intelligence; Chromatography; Chemistry","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":[0.0003744585,0.001121908,0.0005951682,0.0005020768,0.0004556951,0.000744342,0.001752438,0.0008239269,0.005674493],"category_scores_gemma":[0.001123645,0.0004019568,0.000772839,0.0005263978,0.0004666107,0.001757169,0.001248664,0.001525453,0.001674482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000680246,"about_ca_system_score_gemma":0.0007770153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005877766,"about_ca_topic_score_gemma":0.009774268,"domain_scores_codex":[0.9997627,0.000021921,0.00001265159,0.00008809941,0.00008177009,0.00003286601],"domain_scores_gemma":[0.9997995,0.00003646866,0.00001595384,0.00008077263,0.00004557848,0.00002177167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002383027,0.0001470301,0.0008233154,0.0001250861,0.0001034754,0.0001829282,0.0001069595,0.1287262,0.03620386,0.006993647,0.008872177,0.817477],"study_design_scores_gemma":[0.00002954847,0.00005455567,0.0002721986,0.0000103706,0.00001957265,0.00006126177,0.00001460905,0.9786087,0.01317098,0.004467336,0.00327516,0.00001575743],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05645961,0.0008244344,0.9156008,0.0003040541,0.0003885601,0.0001747843,0.0005715343,0.0148058,0.01087053],"genre_scores_gemma":[0.5379903,0.0005508904,0.435036,0.0007387415,0.0001352577,0.0002582378,0.002267567,0.0008745975,0.02214833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005877766,"threshold_uncertainty_score":0.01898301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02271592017030391,"score_gpt":0.2579186612356012,"score_spread":0.2352027410652973,"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."}}