{"id":"W4388561800","doi":"10.1109/dasc58513.2023.10311189","title":"A Hybrid Framework for Object Distance Estimation using a Monocular Camera","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Minimum bounding box; Object detection; Monocular; Range (aeronautics); Bounding overwatch; Pixel; Field of view; Pattern recognition (psychology); Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001307891,0.00008229593,0.00009530469,0.00007818419,0.0001582561,0.0001309363,0.0002704744,0.00001571388,0.000005619228],"category_scores_gemma":[0.0001722086,0.00007510399,0.00005216216,0.0003951397,0.00001545878,0.0005305088,0.00009827498,0.0000615592,0.00004240931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003347429,"about_ca_system_score_gemma":0.00002868629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006543547,"about_ca_topic_score_gemma":3.340693e-7,"domain_scores_codex":[0.9992273,0.00001266196,0.0001294579,0.0002708552,0.0001337234,0.0002260155],"domain_scores_gemma":[0.9994064,0.0001339886,0.00004695371,0.0003184523,0.00004484233,0.00004936591],"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":[0.000008526346,0.00002546325,0.0001246733,0.00003976302,0.00001124496,0.00002133291,0.0005066672,0.02823815,0.001568172,0.2998999,0.001325149,0.668231],"study_design_scores_gemma":[0.00009004259,0.00001112893,0.00006153716,0.00003464822,0.000001523923,0.000004179061,0.00001806372,0.8619841,0.002165551,0.1338986,0.001636371,0.00009429402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002440107,0.00004402392,0.9960241,0.0005400204,0.0002242539,0.0001708301,0.000001778254,0.0004292276,0.000125615],"genre_scores_gemma":[0.1374313,0.000005217654,0.8619453,0.0004128396,0.00002612013,0.00001589161,0.000002494155,0.000008379389,0.0001524458],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8337459,"threshold_uncertainty_score":0.3062652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03211666438954863,"score_gpt":0.3422292206389159,"score_spread":0.3101125562493672,"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."}}