{"id":"W284653500","doi":"10.1117/12.2177535","title":"An infrared-visible image fusion scheme based on NSCT and compressed sensing","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Contourlet; Image fusion; Compressed sensing; Computer science; Artificial intelligence; Weighting; Sparse approximation; Fusion rules; Pyramid (geometry); Pattern recognition (psychology); Algorithm; Wavelet transform; Computer vision; Image (mathematics); Wavelet; Mathematics","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":[0.0005097775,0.00037051,0.0004047169,0.0001671139,0.00007251775,0.0001505192,0.0005786962,0.000192607,0.000008048711],"category_scores_gemma":[0.0004491237,0.0003336199,0.0002467289,0.0003010125,0.0002013268,0.0008517978,0.0001235695,0.0003786079,0.000001386121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001709676,"about_ca_system_score_gemma":0.00002503779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004952664,"about_ca_topic_score_gemma":6.781497e-8,"domain_scores_codex":[0.9980394,2.233089e-8,0.0005465214,0.0003698986,0.0006671917,0.0003769677],"domain_scores_gemma":[0.9980495,0.0001110069,0.0001823707,0.00009723508,0.001330175,0.0002296898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009701317,0.00007958207,0.00009735528,0.000391774,0.00008264202,2.749843e-7,0.0001449559,0.001742143,0.9664332,0.02565519,0.004455293,0.0008206372],"study_design_scores_gemma":[0.0008704269,0.0003133074,0.0001456361,0.0002940665,0.00003584899,0.000007895967,0.0004648465,0.5962859,0.3984463,0.001227416,0.001591708,0.0003166575],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9909429,0.00007151713,0.002592792,0.0003939234,0.0001630137,0.0004967097,0.00003733708,0.0005100371,0.004791774],"genre_scores_gemma":[0.3198659,0.00005802147,0.6794699,0.0001234216,0.0002477694,0.00005035274,0.00001498316,0.0001176714,0.00005205643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6768771,"threshold_uncertainty_score":0.9999116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01206053118762109,"score_gpt":0.2430219907323009,"score_spread":0.2309614595446798,"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."}}