{"id":"W2130147475","doi":"10.1109/mcg.2007.133","title":"Retargeting Images and Video for Preserving Information Saliency","year":2007,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Nokia (Canada)","funders":"National Science Foundation","keywords":"Retargeting; Computer science; Computer vision; Seam carving; Artificial intelligence; Image (mathematics); Image segmentation; Segmentation; Computer graphics (images)","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":[0.0001779378,0.0005037155,0.0003648493,0.0006980002,0.0002221015,0.000426642,0.0004853646,0.0003477586,0.002788096],"category_scores_gemma":[0.001186709,0.0001857712,0.0003352603,0.0004303659,0.0003219524,0.0007577892,0.000481275,0.0003736417,0.0005393089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003037977,"about_ca_system_score_gemma":0.0002119753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001112107,"about_ca_topic_score_gemma":0.001600549,"domain_scores_codex":[0.9998518,0.00001645988,0.000004756955,0.00005320584,0.00005090701,0.00002283994],"domain_scores_gemma":[0.9997311,0.00009231902,0.00003075498,0.00005877345,0.00006274835,0.0000242075],"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":[0.0003271953,0.00005386464,0.0002739076,0.0001918835,0.00003597386,0.0003014813,0.0002082486,0.01221041,0.5557795,0.0077494,0.002499363,0.4203689],"study_design_scores_gemma":[0.0001080149,0.000911155,0.006747638,0.00003658975,0.0001169219,0.001932281,0.0001383247,0.433172,0.5045492,0.02216681,0.03004723,0.00007385111],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09267502,0.0009592524,0.8988848,0.0001650819,0.0001407487,0.0001076773,0.00009085493,0.002030367,0.004946162],"genre_scores_gemma":[0.5774326,0.0007795651,0.4151907,0.0001735122,0.0001545021,0.00007879473,0.0002018569,0.0004391047,0.005549464],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002788096,"threshold_uncertainty_score":0.009327114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131278219035493,"score_gpt":0.26852994615993,"score_spread":0.2554021242563807,"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."}}