{"id":"W4285286563","doi":"10.2316/j.2022.206-0589","title":"DEEP HASHING MULTI-LABEL IMAGE RETRIEVAL WITH ATTENTION MECHANISM, 372-381.","year":2022,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Mechanism (biology); Hash function; Image retrieval; Image (mathematics); Artificial intelligence; Computer security; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002122209,0.00007548062,0.00008652887,0.0001463088,0.0001176821,0.0001314985,0.0001654679,0.0000214251,0.00001801106],"category_scores_gemma":[0.00001391021,0.00007121971,0.00002737425,0.00009635609,0.00001589982,0.0003225169,0.00004455788,0.0001847233,0.000001150467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075241,"about_ca_system_score_gemma":0.00001845773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001701581,"about_ca_topic_score_gemma":8.696979e-7,"domain_scores_codex":[0.9992656,0.00001404708,0.0002501582,0.00006653369,0.0003275042,0.00007618825],"domain_scores_gemma":[0.999492,0.00001720134,0.0001733843,0.00004935331,0.0002367188,0.00003129786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001840374,0.0006547861,0.0005799311,0.0001550713,0.0005750564,0.0001729277,0.001584423,0.4051528,0.4517144,0.03151254,0.0009359819,0.1067781],"study_design_scores_gemma":[0.0005788903,0.00007178954,0.0004820365,0.00004172016,0.00002709547,0.0003156667,0.0001182836,0.9927899,0.003290892,0.002022747,0.000163357,0.00009757278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05540644,0.0001016435,0.9433745,0.0006565066,0.00023716,0.00006201163,0.000005238083,0.00009135376,0.00006510462],"genre_scores_gemma":[0.6835458,0.00005096879,0.3162384,0.00003908117,0.00006533859,0.000003723842,0.00001339389,0.00001528463,0.00002799594],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6281394,"threshold_uncertainty_score":0.2904255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236806761516669,"score_gpt":0.2587122412035198,"score_spread":0.2463441735883531,"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."}}