{"id":"W4386067004","doi":"10.23919/mva57639.2023.10216197","title":"Dynamic Transfer for Domain Adaptation in Crowd Counting","year":2023,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Manitoba","funders":"","keywords":"Computer science; Domain adaptation; Benchmark (surveying); Domain (mathematical analysis); Adaptation (eye); Artificial intelligence; Key (lock); Transfer of learning; Machine learning; Artificial neural network; Data modeling; Data mining; Database; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002359653,0.001252206,0.001525523,0.001345837,0.0009629893,0.001172869,0.002274987,0.001815805,0.002272119],"category_scores_gemma":[0.007058576,0.0005379538,0.001116824,0.001244354,0.001767107,0.002931407,0.003382948,0.002329586,0.0009313284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001211156,"about_ca_system_score_gemma":0.001026224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003732885,"about_ca_topic_score_gemma":0.002220109,"domain_scores_codex":[0.9988512,0.0003685422,0.00003920153,0.0004111421,0.0001985059,0.0001315143],"domain_scores_gemma":[0.9982951,0.0008542013,0.0001676923,0.0003204515,0.0002244573,0.0001381282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001966608,0.0002730337,0.001818686,0.000159725,0.0001232483,0.0003271697,0.0005049712,0.7404661,0.0140359,0.01554007,0.003485742,0.2230687],"study_design_scores_gemma":[0.000008247745,0.00004644659,0.0002881973,0.000009853634,0.000008643325,0.00008073482,0.00005948438,0.9764687,0.003261801,0.01856536,0.001182248,0.00002029687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02242187,0.0003023886,0.9743456,0.000244167,0.00008628255,0.00008029788,0.00006192442,0.0007942265,0.001663261],"genre_scores_gemma":[0.7138041,0.0004801844,0.2786126,0.0005015078,0.0001962421,0.0002881388,0.0004383694,0.0003046645,0.005374256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003732885,"threshold_uncertainty_score":0.01247925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02710659103733413,"score_gpt":0.2726944711241907,"score_spread":0.2455878800868566,"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."}}