{"id":"W2478396075","doi":"10.48550/arxiv.1607.06235","title":"Haze Visibility Enhancement: A Survey and Quantitative Benchmarking","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Visibility; Benchmark (surveying); Benchmarking; Haze; Ground truth; Computer science; Image (mathematics); Image enhancement; Computer vision; Artificial intelligence; Remote sensing; Optics; Geography; Physics; Cartography","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":[0.004468613,0.002269619,0.001677434,0.007344377,0.0006747562,0.0024889,0.002052418,0.001766506,0.001724044],"category_scores_gemma":[0.01717512,0.0007952698,0.001106096,0.005028731,0.001130352,0.003296316,0.001526106,0.001484036,0.001102098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007824005,"about_ca_system_score_gemma":0.0007935098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002499915,"about_ca_topic_score_gemma":0.002444762,"domain_scores_codex":[0.9948075,0.0009370043,0.0003975167,0.00103887,0.00263127,0.00018778],"domain_scores_gemma":[0.9899015,0.005263593,0.0008808434,0.001325497,0.002414091,0.000214508],"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":[0.0002765775,0.0003045119,0.006353292,0.008958377,0.0004156338,0.0001089038,0.0003317916,0.03988167,0.02470642,0.004605269,0.0164644,0.8975931],"study_design_scores_gemma":[0.0001076888,0.002132607,0.03678114,0.006401254,0.0008838782,0.004826158,0.001666477,0.5252198,0.1953676,0.02423612,0.2017848,0.0005923521],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.06370571,0.2106051,0.6961634,0.001066404,0.000626924,0.0006448895,0.003039191,0.006233218,0.01791526],"genre_scores_gemma":[0.3164943,0.1243433,0.539956,0.0006033276,0.0005975188,0.0005136456,0.009910636,0.002587119,0.004994097],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.007344377,"threshold_uncertainty_score":0.02363259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09210372285924155,"score_gpt":0.2331432360318526,"score_spread":0.141039513172611,"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."}}