{"id":"W1929119683","doi":"10.1109/icip.1999.821683","title":"Backpropagation algorithm for multiresolution image classification","year":2003,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Backpropagation; Artificial neural network; Computer science; Artificial intelligence; Image (mathematics); Contextual image classification; Pattern recognition (psychology); Algorithm; Multiresolution analysis; Wavelet transform; Wavelet","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":[0.0000944732,0.00006313748,0.00004596759,0.00003306666,0.00007372428,0.00003447798,0.00004427258,0.00004252861,0.00002536067],"category_scores_gemma":[0.00001557446,0.00006328211,0.00002434467,0.00009654744,0.00001488167,0.0001354659,0.000002232626,0.00003715651,0.00002706267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004116248,"about_ca_system_score_gemma":0.000007582222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001394795,"about_ca_topic_score_gemma":5.858255e-7,"domain_scores_codex":[0.9996363,0.000004970198,0.000110987,0.00009671233,0.00004297436,0.0001080627],"domain_scores_gemma":[0.9997651,0.00001347393,0.00001596534,0.0001136595,0.00006974983,0.00002202801],"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":[8.884902e-7,0.0000442326,0.000008378395,0.00006020689,0.00000781465,8.696676e-8,0.00004115414,0.0001083137,0.2377506,0.04050473,0.01432022,0.7071534],"study_design_scores_gemma":[0.0001232232,0.000007038435,0.00007401737,0.000004356296,0.000005557427,0.000001554322,0.00002155843,0.8210577,0.1429696,0.004046035,0.031592,0.00009727978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002168898,0.00004013295,0.9845802,0.00005424569,0.00004278947,0.0002854434,0.000005798227,0.0007182116,0.01405634],"genre_scores_gemma":[0.141688,0.00001701457,0.8575004,0.00002016385,0.00002761907,0.000326757,0.00003659496,0.00001965638,0.0003637973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8209494,"threshold_uncertainty_score":0.258057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02049040811671585,"score_gpt":0.2661477257602805,"score_spread":0.2456573176435646,"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."}}