Respiratory sound classification on ICBHI
79.34SpecificityNguyen et al. (CoTuning)
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Nguyen et al. (CoTuning)Ext. Dataset=ImageNet, # of Parameters (in M)=23 (estimated)2022.10 | 79.34 | 37.24 | 58.29 | |
| Nguyen et al. (StochNorm)Ext. Dataset=ImageNet, # of Parameters (in M)=23 (estimated)2022.10 | 78.86 | 36.4 | 57.63 | |
| CEBackbone=CNN6, Ext. Dataset=None, # of Parameters (in M)=4.32022.10 | 76.72 | 31.12 | 53.92 | |
| Nguyen et al. (Vanilla)Ext. Dataset=ImageNet, # of Parameters (in M)=23 (estimated)2022.10 | 76.33 | 37.37 | 56.85 | |
| SCLBackbone=CNN6, Ext. Dataset=None, # of Parameters (in M)=4.32022.10 | 76.17 | 27.97 | 52.08 | |
| SCLBackbone=CNN6, Ext. Dataset=AudioSet, # of Parameters (in M)=4.32022.10 | 75.95 | 39.15 | 57.55 | |
| HybridBackbone=CNN6, Ext. Dataset=None, # of Parameters (in M)=4.32022.10 | 75.35 | 33.84 | 54.74 | |
| RespireNetExt. Dataset=ImageNet, # of Parameters (in M)=21 (estimated)2022.10 | 72.3 | 40.1 | 56.2 | |
| LungAttnExt. Dataset=None, # of Parameters (in M)=0.72022.10 | 71.44 | 36.36 | 53.9 | |
| HybridBackbone=CNN6, Ext. Dataset=AudioSet, # of Parameters (in M)=4.32022.10 | 70.47 | 43.29 | 56.89 | |
| Wang et al.Ext. Dataset=ImageNet, # of Parameters (in M)=25 (estimated)2022.10 | 70.4 | 40.2 | 55.3 | |
| CEBackbone=CNN6, Ext. Dataset=AudioSet, # of Parameters (in M)=4.32022.10 | 70.09 | 40.39 | 55.24 | |
| ARSC-NetExt. Dataset=ImageNet2022.10 | 67.13 | 46.38 | 56.76 | |
| LungRN+NLExt. Dataset=None2022.10 | 63.2 | 41.3 | 52.3 |