{"id":"W4283815594","doi":"10.1609/aaai.v36i3.20276","title":"Efficient Model-Driven Network for Shadow Removal","year":2022,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Science and Technology of China; National Natural Science Foundation of China","keywords":"Shadow (psychology); Interpretability; Computer science; Artificial intelligence; Convolutional neural network; Task (project management); Computer vision; Deep learning; Point (geometry); Shadow mapping; FLOPS; Image (mathematics); Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008635699,0.0002210216,0.000251764,0.0001090134,0.0006108226,0.000169839,0.003185766,0.00004722757,0.00004923288],"category_scores_gemma":[0.0001596845,0.0001882701,0.0001700963,0.0007266857,0.0001549472,0.0001530955,0.001233623,0.0003251895,0.00001247049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001242835,"about_ca_system_score_gemma":0.0001333921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001219781,"about_ca_topic_score_gemma":0.000002364034,"domain_scores_codex":[0.9976817,0.00002106677,0.0005186461,0.0005929428,0.0006904626,0.0004951836],"domain_scores_gemma":[0.9985478,0.00008003751,0.0004102767,0.0003979679,0.0005005616,0.00006337686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000656811,0.0001420222,0.00001036818,0.00001927424,0.000009205955,4.425995e-7,0.0006612646,0.06080203,0.02442842,0.8900803,0.001739778,0.02204116],"study_design_scores_gemma":[0.00001975057,0.0002006314,0.000003144122,0.00004012789,0.000006672545,0.000004490649,0.00009297633,0.6983266,0.1377461,0.1631257,0.0002745321,0.0001592147],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02614268,0.00002413891,0.9595757,0.00350579,0.0006201451,0.001286888,0.00001694189,0.0003010445,0.008526659],"genre_scores_gemma":[0.8894275,0.000005139818,0.1092837,0.0004285956,0.00007312124,0.0002986764,8.743523e-7,0.00001680014,0.0004654986],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8632849,"threshold_uncertainty_score":0.7677431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07048946113948087,"score_gpt":0.2968550373924375,"score_spread":0.2263655762529566,"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."}}