{"id":"W4401041662","doi":"10.1109/tii.2024.3424197","title":"Attention-Based Deep Neural Network Combined Local and Global Features for Indoor Scene Recognition","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; China University of Geosciences; Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; Artificial neural network; Computer vision; Deep neural networks; Pattern recognition (psychology)","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":[0.0002048758,0.0001528262,0.0001572957,0.00007705748,0.0002846601,0.0002551689,0.00006088897,0.0002132078,0.00007792401],"category_scores_gemma":[0.000009029195,0.0001226332,0.00009693093,0.0003023366,0.00007522974,0.0002446317,2.747184e-7,0.0003037475,0.00003608039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001500775,"about_ca_system_score_gemma":0.00006448021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003806648,"about_ca_topic_score_gemma":0.0009177328,"domain_scores_codex":[0.9990954,0.00004065499,0.0003241282,0.0001126244,0.0001699698,0.0002572145],"domain_scores_gemma":[0.9994172,0.0002746438,0.00005307915,0.00009181319,0.00004057577,0.0001226829],"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":[0.0003565837,0.00001332422,0.0002784053,0.00004233486,0.00003969244,0.000002274292,0.00005978826,0.1859546,3.970125e-7,0.000003960552,0.0008860924,0.8123626],"study_design_scores_gemma":[0.001392053,0.0005042516,0.0009671599,0.0001284657,0.0001024498,0.00002587814,0.0001719513,0.9949797,0.0000748795,0.0002376911,0.001222615,0.0001928632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3525806,0.000134504,0.636857,0.0007451856,0.006411153,0.0008462137,0.001226434,0.0003019738,0.0008968525],"genre_scores_gemma":[0.9972499,0.00001751365,0.001800794,0.0003200743,0.0002572678,0.000001645463,0.0003091382,0.000004538903,0.00003913325],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8121697,"threshold_uncertainty_score":0.5000835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03380562032507523,"score_gpt":0.2382799357194975,"score_spread":0.2044743153944223,"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."}}