To visualise experiments logs in tensorbard run the following line:
tensorboard --logdir='./logs/'
docker build ./config
docker run -it --rm --env CUDA_VISIBLE_DEVICE=0 --gpus all -v /home/sd20/workspace:/workspace -v /home/sd20/workspace/data:/data/ --workdir=/workspace stgcn
docker tag 267a0d195121 stgcn
ST-GCN - Gadgil et al 2020, Spatio-Temporal Graph Convolution for Functional MRI Analysis
MS-G3D - Liu et al 2020, Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
Multi-layer Perceptron (MLP) classifier
| Model | Data | Input Features | Architecture | Train-accuracy | Validation-accuracy | Remarks |
|---|---|---|---|---|---|---|
| ST-GCN | cov matrix - 22 ROIs | 253 | (64,64,1) | 0.828 | 0.752 | 5-folds average, SGD 1e-2 |
| ours | ICA15 | 105 | (64,64,1) | 1.00 | 0.847 | dropout 0.5, Adam 1e-4 |
| ours | ICA25 | 300 | (64,64,1) | 1.00 | 0.835 | same |
| ours | ICA50 | 1225 | (64,64,1) | 1.00 | 0.902 | same |
| ours | ICA100 | 4950 | (64,64,1) | 1.00 | 0.961 | same |
| ours | ICA200 | 19900 | (64,64,1) | 1.00 | 0.957 | same |
| ours | ICA300 | 44850 | (64,64,1) | 1.00 | 0.968 | same |
Graph Convolution Networks (GCN) classifiers
All results are obtained following a 5-fold cross validation
| Model | Data | Accuracy % (paper) | Batch size | Iterations | Time Window | Remarks |
|---|---|---|---|---|---|---|
| ST-GCN | 22 ROIs | 81.8 (83.7) | 5-folds average, SGD 1e-2 | xxx | 128 | xxx |
| MS-G3D | 22 ROIs | 84.7 | dropout 0.5, Adam 1e-4 | xxx | 50 | xxx |
| MS-G3D | 22 ROIs | 83.0 | dropout 0.0, Adam 1e-3 | 128 | 5k | scale 2, scale 2 |
| Model | Data | Accuracy % | Batch size | Iterations | Time Window | Remarks |
|---|---|---|---|---|---|---|
| ST-GCN | Nodes TS - 15 | 79.8 | 512 | 10k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 15 | 75.9 | 512 | 2k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 15 | 76.7 | 512 | 2k | 75 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 15 | 76.6 | 512 | 2k | 100 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 25 | 82.1 | 512 | 10k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 25 | 78.3 | 512 | 2k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 25 | 79.8 | 512 | 2k | 75 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 25 | 77.8 | 512 | 2k | 100 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 25 | 76.5 | 512 | 2k | 128 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 50 | 86.5 | 512 | 10k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 50 | 82.4 | 512 | 2k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 50 | 81.6 | 512 | 2k | 75 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 50 | 79.6 | 512 | 2k | 100 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 100 | 82.6 | 256 | 2k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 200 | 89.2 | 256 | 2k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 200 | 91.5 | 256 | 10k | 50 | Adam, 1e-3 |
| ST-GCN | Nodes TS - 300 | 87.2 | 128 | 2k | 50 | Adam, 1e-3 |
| Model | Data | Accuracy % | Batch size | Iterations | Time Window | Remarks |
|---|---|---|---|---|---|---|
| MS-G3D | Nodes TS - 15 | 59.1 | 256 | 2k | 10 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 15 | 80.0 | 256 | 2k | 50 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 15 | 80.1 | 256 | 2k | 75 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 15 | 81.5 | 128 | 2k | 100 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 25 | 84.7 | 256 | 2k | 50 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 25 | 85.2 | 128 | 2k | 75 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 25 | 85.1 | 64 | 2k | 100 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 25 | 86.1 | 64 | 5k | 100 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 25 | 85.9 | 64 | 2k | 128 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 25 | 84.3 | 256 | 2k | 50 | Adam, 1e-3, scale g3d 4, scale gcn 4 |
| MS-G3D | Nodes TS - 25 | 84.6 | 256 | 2k | 50 | Adam, 1e-3, scale g3d 1, scale gcn 1 |
| MS-G3D | Nodes TS - 50 | 89.5 | 64 | 2k | 50 | Adam, 1e-3, scale g3d 8, scale gcn 18 |
| MS-G3D | Nodes TS - 50 | 89.3 | 64 | 2k | 75 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 50 | 89.7 | 32 | 2k | 100 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 50 | 90.9 | 32 | 10k | 100 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 50 | 87.9 | 64 | 2k | 50 | Adam, 1e-3, scale g3d 4, scale gcn 1 |
| MS-G3D | Nodes TS - 50 | 89 | 64 | 2k | 50 | Adam, 1e-3, scale g3d 1, scale gcn 1 |
| MS-G3D | Nodes TS - 50 | 87.5 | 64 | 2k | 50 | Adam, 1e-3, scale g3d 1, scale gcn 1 , ws=1 |
| MS-G3D | Nodes TS - 100 | 92.2 | 256 | 2k | 50 | Adam, 1e-3 |
| MS-G3D | Nodes TS - 100 | 93.9 | 32 | 10k | 50 | Adam, 1e-3 |
| MS-G3D-light | Nodes TS - 200 | 94.4 | 128 | 2k | 50 | Adam, 1e-3, scale 1 |
| Train-accuracy | Validation-accuracy | |
|---|---|---|
| ICA15 | xxx | xxx |
| ICA25 | xxx | xxx |
| ICA50 | xxx | xxx |
| ICA100 | xxx | xxx |
| ICA200 | xxx | xxx |
| ICA300 | xxx | xxx |
| Model | Data | Correlation % | Batch size | Iterations | Time Window | Remarks |
|---|---|---|---|---|---|---|
| MS-G3D | Nodes TS - 15 | 28.6 | 256 | 2k | 100 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 15 | 24.1 | 256 | 2k | 75 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 15 | 26.7 | 512 | 2k | 50 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 25 | 30.6 | 64 | 2k | 128 | Adam, 1e-3, scale 8 |
| MS-G3D | Nodes TS - 25 | 28.6 | 128 | 2k | 100 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 25 | 28.0 | 256 | 2k | 75 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 25 | 31.3 | 256 | 2k | 50 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 25 | 0.0714 | 256 | 2k | 50 | new |
| MS-G3D | Nodes TS - 50 | 32.5 | 64 | 2k | 50 | Adam, 1e-3, dropout 0.5, scale 8 |
| MS-G3D | Nodes TS - 50 | 30.7 | 128 | 2k | 50 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 50 | 28.5 | 128 | 2k | 75 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 50 | 30.2 | 64 | 2k | 100 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D | Nodes TS - 100 | 31.7 | 32 | 2k | 50 | Adam, 1e-3, scale 8 |
| MS-G3D | Nodes TS - 100 | 31.3 | 64 | 2k | 50 | Adam, 1e-3, dropout 0, scale 2 |
| MS-G3D-light | Nodes TS - 200 | 32.4 | 16 | 2k | 50 | Adam, 1e-3, scale 1 |