{"id":"W1775416118","doi":"10.1109/dcc.2003.1194045","title":"Image foveation based on vector quantization","year":2003,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Vector quantization; Computer vision; Artificial intelligence; Quantization (signal processing); Fixation (population genetics); Computer science; Retransmission; Mathematics; Pattern recognition (psychology); Transmission (telecommunications)","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":[0.0003080921,0.0002948531,0.0004496548,0.0003642147,0.0002699237,0.0006052612,0.0006289033,0.0003721009,0.007844291],"category_scores_gemma":[0.00121475,0.0001458122,0.000201427,0.0004565178,0.0004589873,0.0009405279,0.0006915909,0.0004052976,0.001291943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004621511,"about_ca_system_score_gemma":0.0002984534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001634232,"about_ca_topic_score_gemma":0.001552528,"domain_scores_codex":[0.9997386,0.00004349386,0.00001231243,0.00006198478,0.0001169815,0.00002661015],"domain_scores_gemma":[0.9995556,0.0001584571,0.00003575153,0.00009450685,0.0001287311,0.00002691761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007681143,0.0000730642,0.0006755758,0.0003175996,0.00005101919,0.0004666582,0.0002145957,0.03048831,0.2402285,0.03335205,0.0146445,0.6787199],"study_design_scores_gemma":[0.0001370031,0.0006668263,0.002447748,0.0001434181,0.0001150835,0.002034452,0.0001281638,0.7227816,0.1822173,0.02564436,0.06356972,0.0001144074],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06044842,0.00575878,0.9082474,0.0005279719,0.0004735128,0.000125115,0.0001517417,0.003457442,0.02080975],"genre_scores_gemma":[0.7611701,0.002613995,0.2161406,0.0002255115,0.0002899624,0.00006194964,0.0002314627,0.0001943727,0.01907198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007844291,"threshold_uncertainty_score":0.02624178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009264051385389514,"score_gpt":0.2407239305476912,"score_spread":0.2314598791623017,"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."}}