{"id":"W2116022029","doi":"10.1109/wescan.1997.627119","title":"Image compression through fractal surface interpolation and wavelet compression","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Fractal transform; Fractal compression; Fractal; Mathematics; Wavelet; Fractional Brownian motion; Affine transformation; Interpolation (computer graphics); Lossless compression; Nearest-neighbor interpolation; Computer vision; Data compression; Artificial intelligence; Image compression; Algorithm; Mathematical analysis; Linear interpolation; Geometry; Computer science; Image processing; Image (mathematics); Brownian motion","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":[0.0003628273,0.0003686606,0.00037532,0.0008975113,0.0001917781,0.0004459581,0.0003712219,0.0003191132,0.001432361],"category_scores_gemma":[0.0009568152,0.0001323555,0.0003767711,0.0009051688,0.0005125917,0.0007601362,0.0004549085,0.0004890479,0.0004556346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001983538,"about_ca_system_score_gemma":0.0001285877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002884089,"about_ca_topic_score_gemma":0.0002812945,"domain_scores_codex":[0.9997872,0.00002508532,0.00001068133,0.00002553536,0.0001333594,0.00001812525],"domain_scores_gemma":[0.9997568,0.00009365896,0.00002585527,0.0000563699,0.00005859675,0.000008696434],"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":[0.0002357555,0.00008273904,0.000558443,0.000251243,0.00003346749,0.0003084962,0.0002021974,0.04131736,0.3072369,0.05619312,0.002216224,0.5913641],"study_design_scores_gemma":[0.00003890638,0.000327501,0.00183928,0.00004348291,0.0000375435,0.001327652,0.00006606191,0.6487889,0.3008176,0.02438945,0.02227685,0.0000467297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03447211,0.0006447129,0.9598033,0.0001811149,0.00009436763,0.00005875154,0.0000497109,0.0006990309,0.003996904],"genre_scores_gemma":[0.3291795,0.001302581,0.6634593,0.0001001146,0.0001741629,0.00006675382,0.0002320876,0.0002203217,0.005265251],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001432361,"threshold_uncertainty_score":0.004791737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03303314828729729,"score_gpt":0.2914520674845834,"score_spread":0.2584189191972861,"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."}}