{"id":"W2547347261","doi":"","title":"Mosaic of near ground UAV videos under parallax effects","year":2012,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Parallax; Computer vision; Computer science; Artificial intelligence; Mosaic; Remote sensing; Aerial survey; Ground truth; Aerial imagery; Aerial image; Aerial photos; Computer graphics (images); Image (mathematics); Geography","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":[0.0001818252,0.0002996615,0.0002413688,0.0005337493,0.000199691,0.000309605,0.0002029995,0.0002082801,0.001259797],"category_scores_gemma":[0.0004610911,0.0001517233,0.0002665053,0.0005292544,0.0002005315,0.0003600804,0.0003149117,0.000245348,0.0002853737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002047237,"about_ca_system_score_gemma":0.0002322544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003174891,"about_ca_topic_score_gemma":0.005976048,"domain_scores_codex":[0.9998994,0.00001270483,0.000003105463,0.0000265352,0.00003674697,0.00002153126],"domain_scores_gemma":[0.999838,0.00002549342,0.00001735063,0.00004314395,0.00005054677,0.00002538752],"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":[0.001022349,0.0001309224,0.009135345,0.0002377416,0.0001849865,0.001091601,0.0002939314,0.2212679,0.4634254,0.002521749,0.005724526,0.2949636],"study_design_scores_gemma":[0.00004426273,0.0002033871,0.03396014,0.0000314412,0.00004496921,0.0008464085,0.0002741118,0.8734461,0.08216873,0.003304832,0.005644917,0.00003063202],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7101504,0.0002565853,0.2807079,0.0001925094,0.000109271,0.00009663765,0.001098494,0.002022255,0.005365892],"genre_scores_gemma":[0.9065359,0.0001108231,0.09088856,0.00003022652,0.00002931627,0.00001345226,0.001225112,0.0001075411,0.001059096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003174891,"threshold_uncertainty_score":0.006312847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008880513870157874,"score_gpt":0.2041173489156961,"score_spread":0.1952368350455382,"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."}}