{"id":"W4385299273","doi":"10.1145/3603781.3603912","title":"A Conformer-Based Hashing Method for Large-Scale Image Retrieval","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Convolutional neural network; Hash function; Image retrieval; Artificial intelligence; Entropy (arrow of time); Pattern recognition (psychology); Deep learning; Locality-sensitive hashing; Hash table; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008263415,0.0006711166,0.000992634,0.001264445,0.0004853529,0.0006302611,0.001216811,0.0007076791,0.002634299],"category_scores_gemma":[0.00211078,0.0002807921,0.00057391,0.00136664,0.0006068127,0.002667941,0.001350653,0.0007466919,0.001344666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006150796,"about_ca_system_score_gemma":0.0008862578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001986305,"about_ca_topic_score_gemma":0.002057532,"domain_scores_codex":[0.9991316,0.0001063683,0.0000628555,0.0001993642,0.0004306511,0.0000691212],"domain_scores_gemma":[0.9993895,0.00008203006,0.00007896921,0.0002157738,0.0002009793,0.00003264347],"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":[0.0002940286,0.0001387463,0.001078356,0.0001706524,0.00008672367,0.00008876064,0.00009085781,0.04018624,0.05508219,0.01707443,0.006813833,0.8788952],"study_design_scores_gemma":[0.00006810214,0.0004251055,0.001284034,0.00001959139,0.00006750157,0.000821924,0.00006563325,0.9144521,0.05456068,0.01667394,0.01147049,0.00009089794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01878221,0.0009374624,0.9764444,0.0001409879,0.000115757,0.0001360058,0.0001348216,0.001448091,0.001860314],"genre_scores_gemma":[0.533641,0.0009973439,0.452859,0.0003490089,0.0002263317,0.000220203,0.0009063036,0.0001722552,0.01062862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002634299,"threshold_uncertainty_score":0.008812547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02883892971898745,"score_gpt":0.3597612077055907,"score_spread":0.3309222779866032,"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."}}