{"id":"W2070431494","doi":"10.1109/iscas.2013.6571994","title":"Salient object cutout using Google images","year":2013,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Object (grammar); Segmentation; Image segmentation; Region of interest; Pixel; Object detection; Cut; Image (mathematics); Graph; Image retrieval; Salient; Segmentation-based object categorization; Pattern recognition (psychology); Information retrieval; Scale-space segmentation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005760484,0.002858734,0.001560285,0.006834641,0.0006174743,0.001107771,0.001724521,0.001396839,0.003664894],"category_scores_gemma":[0.001917849,0.0006504615,0.001384187,0.002056403,0.000551211,0.00135171,0.001477139,0.0007197024,0.001698026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009863451,"about_ca_system_score_gemma":0.0008038986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687927,"about_ca_topic_score_gemma":0.02926051,"domain_scores_codex":[0.9994711,0.00003429334,0.00002185452,0.0002058501,0.0001744665,0.00009254841],"domain_scores_gemma":[0.9993813,0.0001557716,0.00006566238,0.0001101518,0.0002247756,0.00006228569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001525021,0.0003247686,0.002627685,0.0009319495,0.0002050363,0.00102964,0.0003755164,0.02780929,0.1013667,0.002060074,0.03934116,0.8224031],"study_design_scores_gemma":[0.0003091001,0.0005799475,0.0113259,0.0001109405,0.0001803668,0.001605058,0.0005604007,0.8316327,0.1209733,0.008697201,0.02391522,0.0001098708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2424389,0.004447557,0.6452289,0.000608688,0.0005299498,0.002061819,0.005680557,0.08916933,0.009834362],"genre_scores_gemma":[0.3832308,0.000813077,0.5943516,0.000250025,0.0001687078,0.0003380517,0.01374028,0.00210636,0.005001036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01687927,"threshold_uncertainty_score":0.033562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02215271355191564,"score_gpt":0.2752571947291162,"score_spread":0.2531044811772005,"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."}}