{"id":"W4299364625","doi":"","title":"Subpixel image registration for coherent change detection between two high resolution sonar passes","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Subpixel rendering; Image registration; Computer science; Computer vision; Artificial intelligence; Remote sensing; Image resolution; Change detection; Image processing; Image (mathematics); Geology; Pixel","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":[0.0007020339,0.0008760351,0.00100555,0.001482155,0.0004806098,0.001056865,0.0008313333,0.001154658,0.00574197],"category_scores_gemma":[0.002343685,0.0007954267,0.0005678455,0.00144067,0.000481601,0.001299161,0.001480258,0.0009390076,0.003298709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003675288,"about_ca_system_score_gemma":0.0008559476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001333027,"about_ca_topic_score_gemma":0.003493787,"domain_scores_codex":[0.9991527,0.000137115,0.00004353417,0.0002274263,0.0003329038,0.0001062644],"domain_scores_gemma":[0.999123,0.0002138517,0.0001059097,0.0003076145,0.0002011721,0.00004841451],"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":[0.000937834,0.0001889974,0.001775653,0.0002123291,0.00009084023,0.0001791483,0.0002166256,0.01764718,0.3645053,0.003891448,0.003948044,0.6064067],"study_design_scores_gemma":[0.00007064547,0.000360587,0.01101409,0.00003118337,0.0001127085,0.0008882765,0.0001408652,0.6820292,0.2882016,0.004510486,0.01257469,0.00006561043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04871988,0.0003477237,0.9459914,0.0001182393,0.00009975577,0.00008816876,0.0001863379,0.0022918,0.002156831],"genre_scores_gemma":[0.2446326,0.0002620064,0.7490838,0.00009447313,0.00007433945,0.0001342629,0.0007582747,0.0005053584,0.004454875],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00574197,"threshold_uncertainty_score":0.01920885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05497118534624013,"score_gpt":0.2730463652420232,"score_spread":0.2180751798957831,"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."}}