Fine Grained Image Classification On Compcars

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
Resnet50 + PMAL	99.1%	Progressive Multi-task Anti-Noise Learning and Distilling Frameworks for Fine-grained Vehicle Recognition
ResNet101-swp	97.6%	Deep CNNs With Spatially Weighted Pooling for Fine-Grained Car Recognition
Fine-Tuning DARTS	95.9%	Fine-Tuning DARTS for Image Classification
Resnet50 + COOC	95.6%	Fine-Grained Vehicle Classification with Unsupervised Parts Co-occurrence Learning
A3M	95.4%	Attribute-Aware Attention Model for Fine-grained Representation Learning
GoogLeNet	91.2%	A Large-Scale Car Dataset for Fine-Grained Categorization and Verification
AlexNet	81.9%	A Large-Scale Car Dataset for Fine-Grained Categorization and Verification

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Fine Grained Image Classification On Compcars | SOTA | HyperAI