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ResearchFormerly WizWand

Image Classification on Flower

95.84AccuracyDenseNet-121
18.25638.39858.5478.682Apr 10, 2023Oct 3, 2023Mar 28, 2024Sep 21, 2024Mar 16, 2025Sep 9, 2025Mar 5, 2026
Updated 7mo ago

Evaluation results

MethodLinks
DenseNet-121Flower Class=16, Total Count=157422026.0195.84
MobileNetFlower Class=16, Total Count=157422026.0195.58
XceptionFlower Class=16, Total Count=157422026.0195.33
Method from [35]Flower Class=5, Total Count=43232026.0191
CAD-CAMBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0349.67
CADBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0347.88
SEALEvaluation Protocol=linear probe, Generations (G)=102023.0445.68
DIRKBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0344.03
ABLEBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0343.51
CP-DPLLBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0342.42
PRODENBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0341.28
IDGPBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0341.26
RCBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0341.2
CCBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0340.92
CAVLBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0340.69
CELBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0338.51
NormalEvaluation Protocol=linear probe, Generations (G)=12023.0434.31
PICOBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0333.76
POPBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0333.02
VALENBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0332.89
Normal (long)Evaluation Protocol=linear probe, Generations (G)=102023.0426.96
LLFEvaluation Protocol=linear probe, Generations (G)=102023.0422.84
LWSBackbone=ResNet34, Optimizer=SGD, Learning rate=0.01, Weight decay=0.001, Momentum=0.9, Epochs=500, Batch size=162026.0321.24