{"id":"W4412713258","doi":"10.1109/icicv64824.2025.11085854","title":"Multimodal Low-Light Image Enhancement using Retinex-based Decomposition and Transformer Networks","year":2025,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Color constancy; Computer science; Computer vision; Artificial intelligence; Image enhancement; Transformer; Decomposition; Image (mathematics); Engineering","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":[0.000372236,0.0007281823,0.0004417464,0.0006181293,0.0001763304,0.0005644307,0.0005231994,0.000312259,0.001663919],"category_scores_gemma":[0.0005441777,0.0001947361,0.0005555363,0.0003974256,0.0003853297,0.0007828033,0.0007005976,0.0005223003,0.0005040464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004497971,"about_ca_system_score_gemma":0.0002910796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001273977,"about_ca_topic_score_gemma":0.002055086,"domain_scores_codex":[0.9998184,0.00004434471,0.000006691564,0.00003749508,0.00006717021,0.00002592796],"domain_scores_gemma":[0.99983,0.00004704844,0.00002533207,0.00002791952,0.00005486945,0.0000148186],"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":[0.0004427896,0.0001816475,0.0008640209,0.0001809861,0.0001267097,0.0002440857,0.0001403232,0.2305819,0.3179623,0.01767018,0.002872904,0.4287322],"study_design_scores_gemma":[0.00001350708,0.00008014341,0.0003653277,0.00001303254,0.00003816497,0.0001898075,0.00002045748,0.9362034,0.05679719,0.003773066,0.002488166,0.00001778024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02218538,0.0002566168,0.9744203,0.00006694799,0.00002337921,0.00003533945,0.00003630192,0.0004089599,0.002566814],"genre_scores_gemma":[0.4660676,0.0007789467,0.5251935,0.0001254673,0.00004753042,0.00008335232,0.0001813266,0.0001565383,0.00736582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001663919,"threshold_uncertainty_score":0.005566359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005237054553555992,"score_gpt":0.2762310689256299,"score_spread":0.2709940143720739,"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."}}