{"id":"W4412762215","doi":"10.54254/2755-2721/2025.po25557","title":"Literature Review on Attention Based Image Enhancement Techniques","year":2025,"lang":"en","type":"article","venue":"Applied and Computational Engineering","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Image enhancement; Computer science; Image (mathematics); Artificial intelligence","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":[0.0004961248,0.00105862,0.0008229186,0.001779874,0.0002796241,0.001065498,0.001207549,0.001301508,0.009693813],"category_scores_gemma":[0.00213722,0.0004796041,0.0008883787,0.002372825,0.0004217329,0.001738275,0.0005990997,0.001032772,0.002654698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003779374,"about_ca_system_score_gemma":0.000589026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001836374,"about_ca_topic_score_gemma":0.001394415,"domain_scores_codex":[0.9996783,0.00004104874,0.00003841578,0.00008437857,0.0001319688,0.0000260386],"domain_scores_gemma":[0.9988135,0.0008408185,0.00006695797,0.00005369071,0.0001989783,0.00002609711],"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":[0.00008141711,0.00007177392,0.0002271378,0.00595913,0.00009359352,0.0001914824,0.0000778875,0.005479062,0.004695132,0.007263352,0.0207574,0.9551026],"study_design_scores_gemma":[0.00005814348,0.0004132338,0.002361469,0.006485493,0.0006155151,0.003826135,0.0002360986,0.04586249,0.01844015,0.02160616,0.8999329,0.0001622274],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003034027,0.8856223,0.09074823,0.00123212,0.001153367,0.00006627919,0.0001639073,0.0005113472,0.01746844],"genre_scores_gemma":[0.03420686,0.8961242,0.05207439,0.001477896,0.002191948,0.0001140978,0.0005875544,0.0002150235,0.01300804],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009693813,"threshold_uncertainty_score":0.03242898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003859047314024367,"score_gpt":0.2106752392103901,"score_spread":0.2068161918963657,"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."}}