{"id":"W2022974420","doi":"10.1109/icip.2014.7025824","title":"Object detection using edge histogram of oriented gradient","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Histogram; Artificial intelligence; Enhanced Data Rates for GSM Evolution; Histogram of oriented gradients; Computer science; Edge detection; Computer vision; Feature (linguistics); Pattern recognition (psychology); Feature extraction; Object detection; Image (mathematics); Image processing","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":[0.0004108264,0.0005188702,0.0008798891,0.002994669,0.0002055442,0.0007264387,0.0007967607,0.0006215543,0.0009076219],"category_scores_gemma":[0.0008805672,0.0003063397,0.0004246965,0.001694096,0.0003464645,0.001361605,0.0005750955,0.0003214169,0.000875363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000260374,"about_ca_system_score_gemma":0.0003554247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001457937,"about_ca_topic_score_gemma":0.001580706,"domain_scores_codex":[0.9995905,0.00004481166,0.00001549131,0.0001025261,0.0001992411,0.00004752278],"domain_scores_gemma":[0.9996828,0.00008177041,0.00004277218,0.0000409895,0.0001248001,0.00002690586],"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":[0.0002683362,0.000139132,0.003530678,0.0002443248,0.0001205029,0.000350845,0.00005958545,0.01117419,0.1611135,0.002885925,0.003867703,0.8162453],"study_design_scores_gemma":[0.00007164813,0.0003874807,0.01812524,0.00004985448,0.0001599179,0.001593333,0.00009679311,0.7335191,0.2236896,0.007406157,0.01476401,0.0001368544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04763156,0.0013552,0.9465927,0.00009427698,0.0001165342,0.00007277564,0.0001449915,0.002193104,0.001798864],"genre_scores_gemma":[0.5192941,0.001798752,0.4748167,0.0002418014,0.0001471291,0.00008385933,0.000659634,0.0001932324,0.002764649],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002994669,"threshold_uncertainty_score":0.00303632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01718069850617266,"score_gpt":0.274979655185077,"score_spread":0.2577989566789043,"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."}}