{"id":"W3003423830","doi":"10.1109/tmm.2020.2971171","title":"Dual Convolutional LSTM Network for Referring Image Segmentation","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Encoder; Focus (optics); Dual (grammatical number); Segmentation; Image segmentation; Intersection (aeronautics); Natural language; Object (grammar)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001572732,0.0001765225,0.0001571853,0.00006546501,0.000374949,0.00008782744,0.00035407,0.00007751896,0.00006951528],"category_scores_gemma":[0.00002538038,0.0001905501,0.0001197095,0.0003658557,0.00005279952,0.0003484878,0.000004071343,0.0003053932,0.0003039661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007207753,"about_ca_system_score_gemma":0.0000672161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006236133,"about_ca_topic_score_gemma":0.00001158893,"domain_scores_codex":[0.9985922,0.00006432397,0.0002772222,0.0004915754,0.0002629173,0.0003117869],"domain_scores_gemma":[0.9988995,0.0004004694,0.00009474799,0.0002922171,0.0001064824,0.0002066453],"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":[0.0001748564,0.0003952573,0.0002366648,0.00007565265,0.0001628515,0.000006661555,0.003251345,0.6898229,0.06766746,0.003098011,0.005405894,0.2297025],"study_design_scores_gemma":[0.0009602084,0.000118394,0.001760588,0.00001053658,0.00002090842,0.00000403762,0.00002137562,0.9848876,0.0105168,0.0002121336,0.001273297,0.0002141161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005699256,0.00001352381,0.9879479,0.00459194,0.0004777981,0.0006007358,0.00006163355,0.0004735782,0.0001335976],"genre_scores_gemma":[0.5473573,0.000003945435,0.4513324,0.0007048288,0.0002320866,0.0002782416,0.00002088928,0.00001789305,0.00005234084],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.541658,"threshold_uncertainty_score":0.7770408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02954615709882722,"score_gpt":0.2871377927065734,"score_spread":0.2575916356077462,"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."}}