{"id":"W4200308169","doi":"10.1109/ictc52510.2021.9620781","title":"Compressed Neural Network for Thermal Array-Based Fall Detection System on Embedded AI","year":2021,"lang":"en","type":"article","venue":"2021 International Conference on Information and Communication Technology Convergence (ICTC)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Information Technology Research Centre; Ministry of Education, Science and Technology","keywords":"Computer science; Pruning; Artificial intelligence; Artificial neural network; Deep learning; ALARM; Constant false alarm rate; False alarm; Real-time computing; Computer vision; Machine learning; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001639985,0.0006334501,0.0003890594,0.0003167759,0.000224211,0.0002623374,0.0007679442,0.0003799271,0.00258794],"category_scores_gemma":[0.0006235383,0.0001559583,0.0002322694,0.0003009829,0.0001429182,0.0005822198,0.0003835877,0.0005483872,0.0006220198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004270426,"about_ca_system_score_gemma":0.0004979811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007595472,"about_ca_topic_score_gemma":0.01030798,"domain_scores_codex":[0.9998515,0.00001445685,0.000009296766,0.00004713513,0.00004832475,0.00002931539],"domain_scores_gemma":[0.9998506,0.00002611048,0.00001398877,0.00001203574,0.0000823591,0.00001495263],"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":[0.0009999105,0.0006682817,0.006643062,0.0003190741,0.0001240603,0.0005026555,0.0001778761,0.1630786,0.07981908,0.001537624,0.01112158,0.7350081],"study_design_scores_gemma":[0.00001455651,0.0001518114,0.001624285,0.00001155843,0.00002649175,0.00006747781,0.00001779757,0.9859399,0.01073026,0.0005625749,0.0008416642,0.00001167429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4137059,0.001869776,0.5567076,0.001076443,0.000620825,0.0002324356,0.0009933478,0.01249198,0.01230171],"genre_scores_gemma":[0.9558194,0.0002452995,0.039003,0.0002515171,0.00004375517,0.0001022877,0.0004681568,0.0000425566,0.004023982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007595472,"threshold_uncertainty_score":0.01510257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02905659715942332,"score_gpt":0.2689580959146937,"score_spread":0.2399014987552703,"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."}}