{"id":"W4416683839","doi":"10.18280/mmep.121024","title":"A Hybrid Multiscale and CNN-Based Fusion Framework for Enhanced SAR–MS Image Integration","year":2025,"lang":"","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Image fusion; Image (mathematics); Fusion; Image processing; Pattern recognition (psychology); Image segmentation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004661826,0.0006874767,0.0006762558,0.0006600274,0.0001959337,0.0006219928,0.0008734443,0.0007122624,0.001738135],"category_scores_gemma":[0.0005286343,0.0003024309,0.0007744798,0.0006248287,0.0002321322,0.001008637,0.001080565,0.000600605,0.000592584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004523316,"about_ca_system_score_gemma":0.0006618968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004756256,"about_ca_topic_score_gemma":0.007800137,"domain_scores_codex":[0.9997788,0.00002075927,0.00001195056,0.00004329787,0.0001155479,0.0000296741],"domain_scores_gemma":[0.999864,0.00001631342,0.00001566951,0.00002053263,0.0000731078,0.0000104349],"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":[0.0002318536,0.0001327356,0.001436167,0.0002135461,0.0002583383,0.0002315584,0.00006988893,0.2802305,0.167073,0.01443513,0.00535334,0.530334],"study_design_scores_gemma":[0.000003300115,0.00002519637,0.0004054804,0.00000708776,0.00002870256,0.00007950162,0.00000541982,0.9852294,0.01071393,0.001700522,0.001790836,0.00001069077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009856882,0.0004227835,0.9871992,0.00009135237,0.0000586214,0.000031708,0.0001103087,0.0005526026,0.001676598],"genre_scores_gemma":[0.339063,0.0009873048,0.6519645,0.000255798,0.0001594296,0.00010619,0.0007280527,0.0002108446,0.006524959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004756256,"threshold_uncertainty_score":0.009457111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01251838851984866,"score_gpt":0.2474042484563719,"score_spread":0.2348858599365233,"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."}}