{"id":"W2967816088","doi":"10.1007/978-3-030-27202-9_29","title":"Emotion Recognition with Spatial Attention and Temporal Softmax Pooling","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Softmax function; Convolutional neural network; Pooling; Pattern recognition (psychology); Residual; Face (sociological concept); Facial recognition system; Invariant (physics); Task (project management)","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":[0.0007566625,0.001032218,0.0008224612,0.0005176545,0.0002596581,0.001177011,0.001180695,0.0006920076,0.007815556],"category_scores_gemma":[0.0008517969,0.0004317134,0.001167392,0.0009976095,0.0002980048,0.001381525,0.001118505,0.0009495816,0.003127456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005261207,"about_ca_system_score_gemma":0.000453819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002754254,"about_ca_topic_score_gemma":0.004877989,"domain_scores_codex":[0.9996991,0.00004130307,0.00001585251,0.0001017868,0.00007537593,0.00006665295],"domain_scores_gemma":[0.9998122,0.00005888347,0.00001397473,0.00004395325,0.00005716311,0.00001379912],"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":[0.0004037659,0.0001333324,0.0004597715,0.0001501106,0.0001814329,0.00005942793,0.00004921339,0.01480934,0.1249512,0.005858689,0.0104695,0.8424742],"study_design_scores_gemma":[0.00002808023,0.0001645514,0.003077053,0.00002840351,0.0001717274,0.0001680217,0.00004459857,0.8833779,0.09187253,0.01310576,0.007918827,0.00004253467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01679942,0.001653368,0.971918,0.0002512629,0.0002685615,0.00005479372,0.0003163534,0.002625737,0.006112533],"genre_scores_gemma":[0.3735986,0.002046406,0.5900699,0.0005015034,0.0004564533,0.0002081332,0.001749852,0.0005335457,0.03083559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007815556,"threshold_uncertainty_score":0.0261457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02772844862193191,"score_gpt":0.2674764839569085,"score_spread":0.2397480353349766,"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."}}