Few-shot Image Classification on CropDiseases CDFSL (test)
98.14AccuracyUniSiam
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| UniSiamShots=502022.07 | 98.14 | — | — | — | — | |
| DeepCluster-v2Shots=502022.07 | 97.04 | — | — | — | — | |
| UniSiamShots=202022.07 | 96.83 | — | — | — | — | |
| SWAVShots=502022.07 | 96.72 | — | — | — | — | |
| BYOLShots=502022.07 | 96.69 | — | — | — | — | |
| DeepCluster-v2Shots=202022.07 | 96.63 | — | — | — | — | |
| SWAVShots=202022.07 | 96.15 | — | — | — | — | |
| BYOLShots=202022.07 | 96.07 | — | — | — | — | |
| SimCLR-v2Shots=502022.07 | 95.8 | — | — | — | — | |
| SeLa-v2Shots=502022.07 | 95.4 | — | — | — | — | |
| SimCLR-v2Shots=202022.07 | 94.92 | — | — | — | — | |
| SeLa-v2Shots=202022.07 | 94.75 | — | — | — | — | |
| SimCLR-v1Shots=502022.07 | 94.49 | — | — | — | — | |
| SupervisedShots=502022.07 | 94.32 | — | — | — | — | |
| SimCLR-v1Shots=202022.07 | 94.03 | — | — | — | — | |
| DeepCluster-v2Shots=52022.07 | 93.63 | — | — | — | — | |
| MoCo-v2Shots=502022.07 | 93.61 | — | — | — | — | |
| PCL-v2Shots=502022.07 | 93.57 | — | — | — | — | |
| SWAVShots=52022.07 | 93.49 | — | — | — | — | |
| SupervisedShots=202022.07 | 93.09 | — | — | — | — | |
| InfoMinShots=502022.07 | 92.93 | — | — | — | — | |
| MoCo-v1Shots=502022.07 | 92.87 | — | — | — | — | |
| BYOLShots=52022.07 | 92.71 | — | — | — | — | |
| InsDisShots=502022.07 | 92.7 | — | — | — | — | |
| PCL-v2Shots=202022.07 | 92.58 | — | — | — | — | |
| InfoMinShots=202022.07 | 92.34 | — | — | — | — | |
| PIRLShots=502022.07 | 92.18 | — | — | — | — | |
| MoCo-v2Shots=202022.07 | 92.12 | — | — | — | — | |
| UniSiamShots=52022.07 | 92.05 | — | — | — | — | |
| InsDisShots=202022.07 | 91.95 | — | — | — | — | |
| MoCo-v1Shots=202022.07 | 91.29 | — | — | — | — | |
| PIRLShots=202022.07 | 91.19 | — | — | — | — | |
| SeLa-v2Shots=52022.07 | 90.96 | — | — | — | — | |
| SimCLR-v2Shots=52022.07 | 90.8 | — | — | — | — | |
| SimCLR-v1Shots=52022.07 | 90.29 | — | — | — | — | |
| SupervisedShots=52022.07 | 89.37 | — | — | — | — | |
| InsDisShots=52022.07 | 88.01 | — | — | — | — | |
| MoCo-v1Shots=52022.07 | 87.87 | — | — | — | — | |
| InfoMinShots=52022.07 | 87.77 | — | — | — | — | |
| MoCo-v2Shots=52022.07 | 87.62 | — | — | — | — | |
| PCL-v2Shots=52022.07 | 87.57 | — | — | — | — | |
| PIRLShots=52022.07 | 86.22 | — | — | — | — | |
| PCL-v1Shots=502022.07 | 82.83 | — | — | — | — | |
| PCL-v1Shots=202022.07 | 80.74 | — | — | — | — | |
| PCL-v1Shots=52022.07 | 72.89 | — | — | — | — | |
| CrossLearning set-up=Transductive2019.11 | — | 90.64 | 95.91 | 97.48 | — | |
| GNNTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 83.12 | — | — | 59.19 | |
| GNN + ATATraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 90.59 | — | — | 67.47 | |
| GNN + FTTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 87.07 | — | — | 60.74 | |
| GNN + LRPTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 86.15 | — | — | 59.23 | |
| Ours_transLearning set-up=Transductive, Embedding network=Mini80_SSL2019.11 | — | 91.79 | 97.38 | 99.5 | — | |
| Pre+LinearUnSup=false, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 89.25 | 95.51 | 97.68 | — | |
| Pre+LinearUnSup=false, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 89.25 | 95.51 | 97.68 | — | |
| Pre+Mean-CentroidUnSup=false, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 87.61 | 93.87 | 94.77 | — | |
| Pre+Mean-CentroidUnSup=false, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 87.61 | 93.87 | 94.77 | — | |
| ProtoNetUnSup=false, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 79.72 | 88.15 | 90.81 | — | |
| ProtoNetUnSup=false, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 79.72 | 88.15 | 90.81 | — | |
| ProtoTransferUnSup=true, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 86.53 | 95.06 | 97.01 | — | |
| ProtoTransferUnSup=true, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 86.53 | 95.06 | 97.01 | — | |
| RelationNetTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 72.86 | — | — | 53.58 | |
| RelationNet + ATATraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 78.2 | — | — | 61.17 | |
| RelationNet + FTTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 75.78 | — | — | 57.57 | |
| RelationNet + LRPTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 74.21 | — | — | 55.01 | |
| TPNTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 81.91 | — | — | 68.39 | |
| TPN + ATATraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 88.15 | — | — | 77.82 | |
| TPN + FTTraining dataset=mini-ImageNet, Number of ways=5-way2021.04 | — | 70.06 | — | — | 56.06 | |
| UMTRA-ProtoNetUnSup=true, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 79.81 | 86.84 | 88.44 | — | |
| UMTRA-ProtoNetUnSup=true, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 79.81 | 86.84 | 88.44 | — | |
| UMTRA-ProtoTuneUnSup=true, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 82.67 | 92.04 | 95.46 | — | |
| UMTRA-ProtoTuneUnSup=true, Backbone=ResNet-10, Training Dataset=mini-ImageNet2020.06 | — | 82.67 | 92.04 | 95.46 | — |