{"id":"W4385834335","doi":"10.1109/access.2023.3305576","title":"UnShadowNet: Illumination Critic Guided Contrastive Learning for Shadow Removal","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Computer science; Artificial intelligence; Shadow (psychology)","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":[0.0007301369,0.001022875,0.0006472394,0.0003001805,0.0002916886,0.0006195366,0.002102358,0.001069684,0.003869792],"category_scores_gemma":[0.002177558,0.000408168,0.0005107462,0.0002534191,0.0009340352,0.001148689,0.001528637,0.002221636,0.0009462549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007937801,"about_ca_system_score_gemma":0.0008374215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00360474,"about_ca_topic_score_gemma":0.006415014,"domain_scores_codex":[0.9996876,0.00005575438,0.000008976368,0.0001092804,0.0000847543,0.00005381939],"domain_scores_gemma":[0.9994273,0.0002323306,0.00005476106,0.0001246461,0.0001133831,0.00004752308],"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":[0.0005430589,0.0002692206,0.001684335,0.0001388755,0.0001189184,0.0001937081,0.0001141184,0.624651,0.03324603,0.009984035,0.01006336,0.3189934],"study_design_scores_gemma":[0.000009886751,0.00004733793,0.0001572472,0.000004527966,0.000005018654,0.00001683187,0.000003536554,0.9926818,0.004654512,0.001748011,0.0006668173,0.000004510941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0431731,0.0005027106,0.9473223,0.0003164469,0.0001334059,0.00007918041,0.0002003522,0.00356569,0.004706891],"genre_scores_gemma":[0.715881,0.000233377,0.2667025,0.0006302194,0.0001255758,0.0001527681,0.00104261,0.0005189881,0.0147131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003869792,"threshold_uncertainty_score":0.01294577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05600335142623282,"score_gpt":0.3614986325934254,"score_spread":0.3054952811671926,"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."}}