{"id":"W3115729019","doi":"10.1145/3426239","title":"Deep Learning Thermal Image Translation for Night Vision Perception","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Image translation; Computer science; Artificial intelligence; Convolutional neural network; Translation (biology); Deep learning; Computer vision; Perception; Grayscale; Image (mathematics); Pattern recognition (psychology)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001584848,0.0001616595,0.0001876206,0.0002607301,0.0002618585,0.0001095151,0.0004580086,0.0001862194,0.00002114224],"category_scores_gemma":[0.00002733418,0.0001506862,0.00006250739,0.0003857712,0.00006718557,0.0003804439,0.00001452256,0.0002693798,0.0000330094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003902848,"about_ca_system_score_gemma":0.00001027768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001010856,"about_ca_topic_score_gemma":0.000002764453,"domain_scores_codex":[0.9988682,0.00004926382,0.0002934754,0.0004325403,0.0001376589,0.0002188933],"domain_scores_gemma":[0.999341,0.00008127577,0.0000824712,0.0003434476,0.000098912,0.00005286379],"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":[0.00002808226,0.00006497732,0.000018239,0.00008230298,0.00002964962,0.000002650361,0.001009515,0.0005773717,0.1355694,0.004130038,0.00004148985,0.8584463],"study_design_scores_gemma":[0.0006133314,0.002492348,0.0000429596,0.0001220011,0.00004221942,0.00003553768,0.001076823,0.7479767,0.221686,0.001996001,0.02340468,0.0005114696],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004541902,0.0002538982,0.9876841,0.005568293,0.0001831924,0.0006598775,0.000001855053,0.001007184,0.00009970633],"genre_scores_gemma":[0.9130991,0.0001959648,0.08627212,0.00008443202,0.00003380529,0.0002213684,0.000003997984,0.00001727981,0.00007197239],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9085572,"threshold_uncertainty_score":0.6144806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176842157346652,"score_gpt":0.2753056018862906,"score_spread":0.253537180312824,"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."}}