What question did this study set out to answer?

To introduce and validate Extended MNIST (EMNIST), a dataset extending the standard MNIST framework to include handwritten uppercase and lowercase letters.

May 1, 2017

EMNIST: Extending MNIST to handwritten letters

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Authors

GCGregory CohenWestern Sydney University SASaeed AfsharWestern Sydney University JTJonathan TapsonUniversity of Cape Town

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Implication

Benchmark analysis demonstrates increased classification difficulty across handwritten digits and letters with EMNIST, indicating a compatible drop-in replacement for computer vision systems.

Key Points

To introduce and validate Extended MNIST (EMNIST), a dataset extending the standard MNIST framework to include handwritten uppercase and lowercase letters.
Extracted and formatted character images from the NIST Special Database 19 using the original MNIST preprocessing and normalization pipeline.
Evaluated baseline classification performance across the expanded character sets using an online Extreme Learning Machine (ELM) algorithm.
Established a larger and more challenging benchmark containing handwritten letters and digits while preserving the exact 28x28 pixel structure of MNIST.
Confirmed dataset consistency through classification performance comparisons between processed NIST digit subsets and original MNIST digits.

Cite This Study

Cohen et al. (2017) studied this question.

synapsesocial.com/papers/69d77184db9d5e1bf4b8a9ad https://doi.org/10.1109/ijcnn.2017.7966217

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Implication

Benchmark analysis demonstrates increased classification difficulty across handwritten digits and letters with EMNIST, indicating a compatible drop-in replacement for computer vision systems.

EMNIST: Extending MNIST to handwritten letters

Discussion

Member takes

Implication

Key Points

Cite This Study

EMNIST: Extending MNIST to handwritten letters

Discussion

Member takes

Implication

Key Points

Cite This Study

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