{"id":"W377503036","doi":"10.1109/mmul.2015.59","title":"Visual Attention Retargeting","year":2015,"lang":"en","type":"article","venue":"IEEE Multimedia","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Retargeting; Seam carving; Computer science; Artificial intelligence; Computer vision; Visualization; Visual attention; Domain (mathematical analysis); Human–computer interaction; Image (mathematics); Psychology; Perception","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":[0.0005828608,0.0007500652,0.0006877715,0.0009468546,0.0003384202,0.0008667005,0.001164934,0.0007677579,0.005124254],"category_scores_gemma":[0.002432741,0.0002443623,0.0005287754,0.0006217133,0.0005824166,0.001442125,0.001443147,0.0009971956,0.00107297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006194093,"about_ca_system_score_gemma":0.0003201914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002359156,"about_ca_topic_score_gemma":0.002447888,"domain_scores_codex":[0.9995547,0.00007482278,0.00001593541,0.0001565578,0.0001351571,0.00006281972],"domain_scores_gemma":[0.99932,0.0003182335,0.00004249195,0.0001173731,0.0001660845,0.00003574252],"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":[0.0002238298,0.00006979255,0.0005391484,0.0005727924,0.00007330978,0.0003263678,0.0004447413,0.01385604,0.1029377,0.03415351,0.01407922,0.8327234],"study_design_scores_gemma":[0.0001254467,0.0007102787,0.007265925,0.0003644356,0.0002654334,0.002446151,0.0004504735,0.4283025,0.158205,0.1840724,0.2175874,0.00020451],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01890952,0.009730265,0.9459794,0.0007680104,0.0005583,0.0001596517,0.0001708425,0.00245661,0.02126741],"genre_scores_gemma":[0.5896964,0.008058102,0.3701157,0.001427056,0.0008483997,0.0002233449,0.0005256232,0.0009051518,0.02820029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005124254,"threshold_uncertainty_score":0.0171423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04202174934340255,"score_gpt":0.3064269274012328,"score_spread":0.2644051780578303,"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."}}