{"id":"W4393040678","doi":"10.3390/ai5010021","title":"Single Image Super Resolution Using Deep Residual Learning","year":2024,"lang":"en","type":"article","venue":"AI","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Toronto Zoo","funders":"","keywords":"Residual; Artificial intelligence; Deep learning; Computer science; Computer vision; Image (mathematics); Pattern recognition (psychology); Algorithm","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":[0.0006081055,0.0005856859,0.000612423,0.0007318538,0.0001535555,0.0005285514,0.0006900954,0.0005355097,0.001990923],"category_scores_gemma":[0.001125658,0.000313188,0.0006746793,0.0005958751,0.0002970817,0.001044958,0.000669369,0.0008883774,0.0007552059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004489922,"about_ca_system_score_gemma":0.0005007913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003327652,"about_ca_topic_score_gemma":0.004828523,"domain_scores_codex":[0.9997657,0.00003117463,0.00001146975,0.00005332825,0.0001104478,0.00002786455],"domain_scores_gemma":[0.9996752,0.00009109421,0.00004617218,0.00006757704,0.0001002048,0.00001979607],"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":[0.0002922147,0.0001523487,0.00106551,0.0001761068,0.0001499527,0.0001618258,0.00007037915,0.3747377,0.07271337,0.005841357,0.004313821,0.5403254],"study_design_scores_gemma":[0.000003767988,0.00002801364,0.0001523924,0.00000503377,0.000008803549,0.00004867982,0.000005447659,0.9895309,0.008418141,0.0010977,0.000695086,0.000005975327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.030031,0.0005353783,0.9652379,0.000167543,0.00004227868,0.0000421513,0.0001661452,0.001703276,0.00207433],"genre_scores_gemma":[0.4214244,0.0007642501,0.5713866,0.0002174925,0.0000446651,0.00006413761,0.0008453377,0.0002167985,0.005036212],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003327652,"threshold_uncertainty_score":0.006660283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091539249879587,"score_gpt":0.304840264488246,"score_spread":0.2839248719894502,"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."}}