{"id":"W2544353392","doi":"10.1109/ichr.2007.4813905","title":"Task-driven moving object detection for robots using visual attention","year":2007,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Object (grammar); Object detection; Probabilistic logic; Motion (physics); Representation (politics); Task (project management); Segmentation; Inference; Robot; Engineering","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":[0.000355295,0.0003666946,0.0004288386,0.0005113644,0.000165753,0.000317961,0.0005707007,0.000443323,0.0005709455],"category_scores_gemma":[0.00112297,0.0002716481,0.0003771902,0.0002594688,0.0002733646,0.0006118069,0.0004480806,0.000290624,0.0001355315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005876399,"about_ca_system_score_gemma":0.0003785327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004393448,"about_ca_topic_score_gemma":0.004226955,"domain_scores_codex":[0.9998564,0.00002996849,0.000004563924,0.00004155352,0.00003914108,0.00002851125],"domain_scores_gemma":[0.9997591,0.0001075857,0.0000362393,0.00002414687,0.00005299253,0.0000198248],"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":[0.0004531699,0.0001497371,0.003301905,0.000169882,0.0001478739,0.0002368423,0.0002085953,0.1785189,0.279716,0.005549757,0.002018088,0.5295293],"study_design_scores_gemma":[0.00001679908,0.00007392492,0.003742309,0.000004786278,0.00001993368,0.00008938742,0.0000151084,0.9757962,0.01519746,0.004431616,0.0005988048,0.00001375809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09337232,0.0004376507,0.9039448,0.00009913197,0.00002912627,0.00003443771,0.00002922151,0.0008620677,0.001191195],"genre_scores_gemma":[0.8742064,0.0001969376,0.1244547,0.00005894086,0.0000340259,0.00003909871,0.00006642858,0.00004648944,0.0008969907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004393448,"threshold_uncertainty_score":0.008735776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02844694135259067,"score_gpt":0.324696811699991,"score_spread":0.2962498703474003,"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."}}