{"id":"W4220891343","doi":"10.18280/ts.390114","title":"Application of Image Processing and Identification Technology for Digital Archive Information Management","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Identification (biology); Digital image processing; Image processing; Histogram; Color management; Adaptive histogram equalization; Information retrieval; Computer vision; Digital image; Projection (relational algebra); Histogram equalization; Document image processing; Computer graphics (images); Image (mathematics); Multimedia; Artificial intelligence; 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":[0.0006457926,0.0002966628,0.0002449969,0.001821823,0.0004204704,0.0009649387,0.0006248013,0.0006151992,0.001963977],"category_scores_gemma":[0.00107454,0.0002081312,0.0003516647,0.001413866,0.0005134098,0.001414199,0.0005880828,0.0005616468,0.0008559068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004247763,"about_ca_system_score_gemma":0.0004445194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007775034,"about_ca_topic_score_gemma":0.0005502344,"domain_scores_codex":[0.9993328,0.0001302478,0.00004829126,0.000107162,0.0003402093,0.00004127211],"domain_scores_gemma":[0.9994259,0.000172951,0.00004978708,0.000131721,0.0001977143,0.000021866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007573977,0.00005706722,0.001474133,0.0002933441,0.00003334506,0.0002398725,0.0003226124,0.004210619,0.09907123,0.01507457,0.00420723,0.8749404],"study_design_scores_gemma":[0.00004096523,0.0004308054,0.009013327,0.0002096056,0.0001814463,0.003125301,0.0005943358,0.2130686,0.4901326,0.02294217,0.2600715,0.0001894039],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02574791,0.003269941,0.9569269,0.0006084792,0.000201802,0.0001107027,0.00004674754,0.001537503,0.01155005],"genre_scores_gemma":[0.2728843,0.004441973,0.7140958,0.000316354,0.0002471555,0.00007815687,0.0001129495,0.0001147943,0.007708516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001963977,"threshold_uncertainty_score":0.00657016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004351580698971883,"score_gpt":0.2078319375860578,"score_spread":0.2034803568870859,"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."}}