{"id":"W2123015911","doi":"10.1109/icip.2009.5414326","title":"Fast vignetting correction and color matching for panoramic image stitching","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vignetting; Image stitching; Artificial intelligence; Computer vision; Computer science; Brightness; Panorama; Color balance; Matching (statistics); Color correction; Image (mathematics); Color image; Image processing; Mathematics; Optics; Lens (geology)","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":[0.0002091087,0.0001042776,0.0001163997,0.0000647942,0.0002095399,0.0002522655,0.0001958766,0.00003627094,0.000001893775],"category_scores_gemma":[0.00007350669,0.00009294177,0.00003274733,0.0001495669,0.00001500648,0.001139943,0.0000665718,0.00009263297,0.00000253562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000289246,"about_ca_system_score_gemma":0.00001353083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000128898,"about_ca_topic_score_gemma":0.000002448606,"domain_scores_codex":[0.9992623,0.00001608981,0.0001519882,0.0002770403,0.00008652213,0.0002060713],"domain_scores_gemma":[0.9995474,0.0001192353,0.00006574276,0.0001627486,0.00005945851,0.00004547435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009573115,0.00001834314,0.00002301743,0.000007765688,0.000002540141,0.000003190909,0.0003486456,0.00001888776,0.0992159,0.009678391,0.0005528828,0.8901209],"study_design_scores_gemma":[0.0008388299,0.00118371,0.002587968,0.0001571823,0.00001612377,0.0001225714,0.0004519725,0.394803,0.4566351,0.1390215,0.003406012,0.0007760517],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01667003,0.00005232982,0.9804249,0.0003934757,0.0001527412,0.0002500819,6.161565e-7,0.0005615125,0.001494294],"genre_scores_gemma":[0.4361396,0.0000163617,0.5628462,0.0005911895,0.00004715281,0.000006304953,0.000001104055,0.00000523163,0.0003468889],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8893448,"threshold_uncertainty_score":0.3790055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008226967082724194,"score_gpt":0.2827560599614676,"score_spread":0.2745290928787434,"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."}}