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K
홈
SOTA
Audio Classification
Audio Classification On Icbhi Respiratory
Audio Classification On Icbhi Respiratory
평가 지표
ICBHI Score
Sensitivity
Specificity
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
ICBHI Score
Sensitivity
Specificity
Paper Title
Repository
DAT (AST)
59.81
42.50
77.11
Stethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification
AST (Patch-Mix CL)
62.37
43.07
81.66
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
-
SG-SCL (AST)
61.71
43.55
79.87
Stethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification
CNN6 (+metadata)
58.04
-
-
Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning
AST (fine-tuning)
-
41.97
77.14
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
-
ResNeSt
55.30
40.20
70.40
A DOMAIN TRANSFER BASED DATA AUGMENTATION METHOD FOR AUTOMATED RESPIRATORY CLASSIFICATION
-
Audio-CLAP
62.56
44.67
80.85
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification
bi-ResNet (scratch)
50.16
31.10
69.20
LungBRN: A Smart Digital Stethoscope for Detecting Respiratory Disease Using bi-ResNet Deep Learning Algorithm
M2D/0.7 (e=0.3)
62.73
-
-
Masked Modeling Duo: Towards a Universal Audio Pre-training Framework
CNN6 (scratch)
54.74
33.84
75.35
Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning
CycleGuardian
63.26
44.47
82.06
CycleGuardian: A Framework for Automatic RespiratorySound classification Based on Improved Deep clustering and Contrastive Learning
AFT on Mixed-500
61.79
42.86
80.72
Adversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalance
ResNet-34
56.20
40.10
72.30
RespireNet: A Deep Neural Network for Accurately Detecting Abnormal Lung Sounds in Limited Data Setting
CNN6
57.55
-
75.95
Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning
CNN6 (+metadata)
-
39.15
76.93
Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning
M2D-X/0.7 (η=0.3)
63.29
-
-
0/1 Deep Neural Networks via Block Coordinate Descent
-
ResNet-50
58.29
37.24
79.34
Lung Sound Classification Using Co-tuning and Stochastic Normalization
-
AST (fine-tuning)
59.55
-
-
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification
-
BTS
63.54
45.67
81.4
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification
bi-ResNet-Att
56.76
46.38
67.13
ARSC-Net: Adventitious Respiratory Sound Classification Network Using Parallel Paths with Channel-Spatial Attention
-
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