{"id":"W2668134242","doi":"10.1007/s11042-017-4938-9","title":"Efficient and secure cryptosystem for fingerprint images in wavelet domain","year":2017,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; Université Laval","funders":"","keywords":"Computer science; Encryption; Robustness (evolution); Cryptosystem; Fingerprint (computing); Permutation (music); Image (mathematics); Integer (computer science); Artificial intelligence; Wavelet; Pattern recognition (psychology); Algorithm; Computer security","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":[0.0001844064,0.00009286861,0.0001197911,0.00005423637,0.000395825,0.0002693606,0.0003514285,0.00004751575,3.01429e-7],"category_scores_gemma":[0.00002201373,0.00008086455,0.00002634004,0.00004721713,0.00009302307,0.0001295836,0.0001897337,0.00006741872,7.036984e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008672294,"about_ca_system_score_gemma":0.000008348045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007885972,"about_ca_topic_score_gemma":0.000005865453,"domain_scores_codex":[0.9993364,0.00001160927,0.0001393039,0.0002940833,0.0000585372,0.0001600535],"domain_scores_gemma":[0.9992501,0.0001146839,0.00008832315,0.0004616219,0.00002990196,0.00005541727],"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":[0.00001301832,0.0001379274,0.004762575,0.0001517854,0.00001257087,0.000004029968,0.001604191,0.00004371532,0.008147292,0.1684795,0.0001609561,0.8164824],"study_design_scores_gemma":[0.004376686,0.0002210135,0.2400959,0.0004879179,0.00002931511,0.00005062306,0.0003324431,0.331088,0.0357552,0.262818,0.1230563,0.00168855],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04146427,0.0001383707,0.9561985,0.0008985282,0.00002760405,0.0008486287,0.0000448295,0.00009079757,0.0002885336],"genre_scores_gemma":[0.6746814,0.00003595134,0.3244147,0.00002946078,0.00003435808,0.000785166,0.000003881245,0.000004453059,0.00001058334],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8147938,"threshold_uncertainty_score":0.3297561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719136722622663,"score_gpt":0.2750324367752295,"score_spread":0.2578410695490029,"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."}}