{"id":"W2073534752","doi":"10.1109/jstars.2014.2308301","title":"Detection of Buildings in Multispectral Very High Spatial Resolution Images Using the Percentage Occupancy Hit-or-Miss Transform","year":2014,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Panchromatic film; Multispectral image; Computer science; Artificial intelligence; Computer vision; Pixel; Transformation (genetics); Image resolution; Object detection; Multispectral pattern recognition; Pattern recognition (psychology); Remote sensing; 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":[0.0004942644,0.0004035094,0.0003453133,0.00181271,0.0001651582,0.0004928946,0.0003224337,0.0003404497,0.0006302963],"category_scores_gemma":[0.000963843,0.0002021266,0.0003855823,0.0009384293,0.0003549503,0.0006515389,0.0004588394,0.0002711189,0.0003321856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001352218,"about_ca_system_score_gemma":0.0001789913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006193819,"about_ca_topic_score_gemma":0.001022371,"domain_scores_codex":[0.999712,0.00006713681,0.00001620811,0.00005511432,0.0001141916,0.00003533845],"domain_scores_gemma":[0.9996319,0.0001164358,0.00008876091,0.00005673984,0.00008213921,0.00002408125],"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":[0.000626738,0.0001554269,0.01583359,0.0003354994,0.0001636754,0.0004956913,0.0002705753,0.03784137,0.3413721,0.003997023,0.001106281,0.5978019],"study_design_scores_gemma":[0.00003082378,0.0004009283,0.06870943,0.00003704692,0.0001388925,0.001971678,0.0002898064,0.7551089,0.1676528,0.002438938,0.003132909,0.00008776154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2728306,0.0002304618,0.7243494,0.00005536787,0.00002563821,0.00005351112,0.000183849,0.000825224,0.001445946],"genre_scores_gemma":[0.696973,0.0002107512,0.3017483,0.00002197129,0.00002670556,0.00003565782,0.0003293823,0.00004633356,0.0006079267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00181271,"threshold_uncertainty_score":0.002613962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02020756670653354,"score_gpt":0.2308675912837053,"score_spread":0.2106600245771718,"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."}}