{"id":"W2098621703","doi":"","title":"METHODS FOR IMAGE FUSION QUALITY ASSESSMENT - A REVIEW, COMPARISON AND ANALYSIS","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Quality assessment; Image fusion; Image quality; Ranking (information retrieval); Standard deviation; Computer science; Artificial intelligence; Fusion; Sensor fusion; Quality (philosophy); Correlation coefficient; Statistics; Pattern recognition (psychology); Mathematics; Image (mathematics); Evaluation methods; Reliability engineering; Engineering","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":[0.01682939,0.001761903,0.002902494,0.01311843,0.0006357275,0.003190796,0.002314854,0.001613914,0.002798403],"category_scores_gemma":[0.0288808,0.0007887401,0.001740421,0.01154298,0.00123205,0.003281838,0.001211775,0.001233011,0.001870524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001228039,"about_ca_system_score_gemma":0.001081593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001799637,"about_ca_topic_score_gemma":0.001362463,"domain_scores_codex":[0.9844574,0.003737079,0.001893219,0.001126161,0.008623971,0.0001621819],"domain_scores_gemma":[0.9732642,0.01569328,0.002383781,0.001438042,0.007083612,0.0001370602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001416869,0.00009650512,0.003553172,0.009127481,0.0004793108,0.0001004078,0.0002383401,0.005589058,0.004459123,0.006444403,0.00441342,0.965357],"study_design_scores_gemma":[0.0003429669,0.002375321,0.05752124,0.01869336,0.003898907,0.01013239,0.002377191,0.2143152,0.08491591,0.06051295,0.5432211,0.001693505],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.006602463,0.407302,0.5748168,0.0006631877,0.0005426177,0.0004778495,0.0005446599,0.0007578328,0.008292507],"genre_scores_gemma":[0.08862621,0.3326574,0.5707309,0.0004475031,0.001098648,0.001433225,0.001349195,0.0003903221,0.003266638],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01682939,"threshold_uncertainty_score":0.08900338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06808736002439475,"score_gpt":0.4824693185722307,"score_spread":0.4143819585478359,"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."}}