{"id":"W2136689788","doi":"10.1007/978-3-319-10602-1_5","title":"Spectral Edge Image Fusion: Theory and Applications","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Structure tensor; Rendering (computer graphics); Artificial intelligence; Contrast (vision); Computer vision; Image fusion; Image (mathematics); Image gradient; Algorithm; Image processing; Edge detection","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003658209,0.0002999812,0.0002639219,0.0003153559,0.0001112724,0.0001001046,0.0005518388,0.0001633391,0.00006745641],"category_scores_gemma":[0.00003019706,0.0002830218,0.00004264673,0.000152379,0.0006119661,0.0001317349,0.0002968685,0.0005139738,0.00002843181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009893087,"about_ca_system_score_gemma":0.0000331021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.387767e-7,"about_ca_topic_score_gemma":0.000005041611,"domain_scores_codex":[0.9987226,0.00001116508,0.0002224955,0.0005249212,0.0002312454,0.0002876065],"domain_scores_gemma":[0.9989548,0.0002671927,0.00005180228,0.0005773898,0.00005965002,0.0000891248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002255413,0.000003285505,0.000002553758,0.00005704563,0.00000311106,0.000009152639,0.00008762334,0.002870255,0.004488867,0.02289652,0.00005917693,0.9695202],"study_design_scores_gemma":[0.0001542426,0.00006973817,0.00005605111,0.0002730633,0.00001224888,0.00008695618,1.890302e-7,0.07310932,0.0255686,0.8742585,0.02555553,0.0008556012],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001751132,0.0006645048,0.984286,0.00004193153,0.0002424341,0.0003461868,0.000005585377,0.000480299,0.01391561],"genre_scores_gemma":[0.03993275,0.0005266343,0.95639,0.0006801144,0.001362328,0.00006411928,0.00001180985,0.0001328028,0.0008994548],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9686645,"threshold_uncertainty_score":0.9999622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005407876286158084,"score_gpt":0.2266117158408992,"score_spread":0.2212038395547411,"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."}}