{"id":"W2028943866","doi":"10.1109/icip.2011.6116447","title":"Image contrast enhancement in compressed wavelet domain","year":2011,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Wavelet; Artificial intelligence; Computer science; Computer vision; Wavelet transform; JPEG; Discrete wavelet transform; Image quality; Stationary wavelet transform; Pattern recognition (psychology); Image (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":[0.0003403031,0.0001453437,0.0001682879,0.000124452,0.0000364656,0.00006821322,0.0008948908,0.00003861798,0.0005639681],"category_scores_gemma":[0.000009561679,0.0001311959,0.00003440613,0.0002353943,0.00005812641,0.0006392158,0.0002809789,0.0001066359,0.0001728786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005607327,"about_ca_system_score_gemma":0.00002625789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001300424,"about_ca_topic_score_gemma":0.00003602383,"domain_scores_codex":[0.9987163,0.00006180374,0.0002858949,0.0003560249,0.0002157963,0.0003641979],"domain_scores_gemma":[0.9992394,0.00002608633,0.00006217621,0.0005660936,0.00005060348,0.00005559539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003875138,0.0011036,0.0005475988,0.00003695863,0.00002816409,0.0002350082,0.004735392,1.380377e-7,0.6729069,0.2631572,0.01575415,0.04145616],"study_design_scores_gemma":[0.0006752802,0.0001400039,0.002649445,0.00002799971,0.000001347778,0.000004127287,0.00004183249,0.004609567,0.9761758,0.01351762,0.001873564,0.0002834069],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007923583,0.00001702779,0.8659432,0.0001831726,0.0001018538,0.0002979939,5.16931e-7,0.0003146202,0.125218],"genre_scores_gemma":[0.4362041,0.000007333267,0.562921,0.000438392,0.000009988669,0.00005614763,0.000001007589,0.000005690809,0.0003562684],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4282806,"threshold_uncertainty_score":0.6175056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0188691543893141,"score_gpt":0.2395053635575081,"score_spread":0.220636209168194,"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."}}