{"id":"W3131333716","doi":"10.1007/s00138-021-01172-y","title":"3MNet: Multi-task, multi-level and multi-channel feature aggregation network for salient object detection","year":2021,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; Salient; Feature (linguistics); Pattern recognition (psychology); Task (project management); Channel (broadcasting); Convolutional neural network; Object detection; Image (mathematics); Object (grammar); Layer (electronics); Computer vision; Engineering","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":[0.0007056648,0.001278355,0.001105159,0.0008638136,0.0006579599,0.0008165925,0.002167932,0.001268953,0.00566696],"category_scores_gemma":[0.001440482,0.0005347895,0.0005928656,0.0008404087,0.0002808456,0.001431921,0.001686271,0.00109047,0.001367093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009222171,"about_ca_system_score_gemma":0.001019325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01042343,"about_ca_topic_score_gemma":0.0233981,"domain_scores_codex":[0.9997366,0.00003494077,0.00001045813,0.0000875265,0.00006621872,0.00006417232],"domain_scores_gemma":[0.999663,0.00008224444,0.00002238549,0.00006754085,0.0001259842,0.00003885883],"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":[0.001165761,0.0006303581,0.00298971,0.0002882942,0.0003807772,0.0003427985,0.0001086119,0.07922658,0.03372423,0.004954915,0.07476625,0.8014216],"study_design_scores_gemma":[0.00004015657,0.0001399731,0.001155462,0.00001172991,0.00003430887,0.00007833415,0.00001730456,0.9819461,0.008500363,0.003013617,0.00504172,0.00002096793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05534436,0.001544076,0.9131046,0.000584372,0.000859765,0.0003270664,0.004118545,0.01945987,0.004657262],"genre_scores_gemma":[0.491383,0.0005995982,0.4766266,0.0008471842,0.0003472237,0.0006119633,0.008868817,0.0006010827,0.02011438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01042343,"threshold_uncertainty_score":0.02072549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03062910536407817,"score_gpt":0.3135120823360417,"score_spread":0.2828829769719635,"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."}}