{"id":"W4311164299","doi":"10.18280/ts.390511","title":"A Deep Transfer Learning Based Visual Complexity Evaluation Approach to Mobile User Interfaces","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Usability; Login; Human–computer interaction; Deep learning; Heuristics; Mobile device; User interface design; User interface; Artificial intelligence; Machine learning; User experience design; Visualization; Transfer of learning; Multimedia; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002180519,0.001091894,0.0005657994,0.002441818,0.000240425,0.001102455,0.0007499315,0.0007589242,0.002565103],"category_scores_gemma":[0.009631532,0.0002343587,0.0007161064,0.0009823013,0.0004417184,0.001606038,0.001277725,0.0009008761,0.0005850084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001276591,"about_ca_system_score_gemma":0.0005313987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003114956,"about_ca_topic_score_gemma":0.00325216,"domain_scores_codex":[0.9978909,0.000695165,0.0001618515,0.000330465,0.0007807949,0.0001407713],"domain_scores_gemma":[0.9960414,0.001530926,0.0003919569,0.0003048409,0.001580578,0.0001502794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008430635,0.0009497268,0.01236574,0.0004742348,0.0002094409,0.0001637761,0.0005590192,0.06418786,0.03000901,0.002999368,0.003794851,0.883444],"study_design_scores_gemma":[0.00003141992,0.0008871428,0.01353187,0.00006257316,0.00007513214,0.0001414955,0.0001967099,0.965757,0.01439996,0.003384017,0.001489715,0.00004291385],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1825784,0.0005860141,0.8071208,0.0002795587,0.00007270402,0.0008829919,0.0004966517,0.002775729,0.005207214],"genre_scores_gemma":[0.8603487,0.0002019323,0.1353914,0.0001092823,0.00003676198,0.000515028,0.0005059081,0.00007923724,0.002811688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003114956,"threshold_uncertainty_score":0.01153183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06810133100677496,"score_gpt":0.3320915283016302,"score_spread":0.2639901972948553,"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."}}