{"id":"W4225523354","doi":"10.3390/jimaging8040110","title":"Salient Object Detection by LTP Texture Characterization on Opposing Color Pairs under SLICO Superpixel Constraint","year":2022,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Color space; Hue; RGB color model; Pattern recognition (psychology); Luminance; RGB color space; Cyan; Color image; Mathematics; Image processing; Image (mathematics); Physics","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":[0.0003004178,0.0005604765,0.0009341603,0.001220306,0.0002635565,0.0007276901,0.0008045438,0.0003784266,0.001633366],"category_scores_gemma":[0.001378574,0.0002440177,0.0005968753,0.0008630797,0.0005313526,0.000858186,0.0007443052,0.0004094203,0.0003811703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005339111,"about_ca_system_score_gemma":0.0007624446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004190139,"about_ca_topic_score_gemma":0.003880646,"domain_scores_codex":[0.999699,0.00002960463,0.00001219652,0.00007610648,0.0001306431,0.00005259674],"domain_scores_gemma":[0.9996073,0.00008035984,0.00006988638,0.00006014198,0.0001354412,0.00004690482],"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":[0.0008317647,0.00009934718,0.003024649,0.0003713546,0.0001051875,0.0006275241,0.00028756,0.1414532,0.3116539,0.01978749,0.004199476,0.5175585],"study_design_scores_gemma":[0.00001387061,0.00006243647,0.001763667,0.000008097255,0.00002406339,0.0001845989,0.0000373996,0.9678388,0.02285323,0.005993553,0.001205469,0.00001485021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07660064,0.0002134462,0.9206035,0.00007372254,0.00002589875,0.00006460122,0.0001422726,0.0005682005,0.001707788],"genre_scores_gemma":[0.7153009,0.0002808025,0.281461,0.00008747464,0.00005908053,0.0001165445,0.0005000035,0.0002190234,0.001975183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004190139,"threshold_uncertainty_score":0.008331537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03783478886263522,"score_gpt":0.1797147184729335,"score_spread":0.1418799296102983,"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."}}