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3 months ago

Fer2013 Recognition - ResNet18 With Tricks

{Xiaojian Yuan}

Abstract

This work is the final project of the Computer Vision Course of USTC. However, I achieve the highest single-network classification accuracy on FER2013 based on ResNet18. To my best knowledge, this work achieves state-of-the-art single-network accuracy of 73.70 % on FER2013 without using extra training data, which exceeds the previous work [1] of 73.28%.

Benchmarks

BenchmarkMethodologyMetrics
facial-expression-recognition-on-fer2013ResNet18 With Tricks
Accuracy: 73.70

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Fer2013 Recognition - ResNet18 With Tricks | Papers | HyperAI