% Test Accuracy: 54.7
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Sequential Image Classification
Sequential image classification is the task of classifying a sequence of images.
<span style="color:grey; opacity: 0.6">( Image credit: TensorFlow-101 )</span>
논문
Unpermuted Accuracy: 99.32%Permuted Accuracy: 98.54%
% Test Accuracy: 59.0
% Test Accuracy: 69.87%
% Test Accuracy: 59.0
% Test Accuracy: 60.5
% Test Accuracy: 62.4
Unpermuted Accuracy: 99.3%Permuted Accuracy: 96.96%
Unpermuted Accuracy: 99.0%Permuted Accuracy: 97.2%
Unpermuted Accuracy: 99.53%Permuted Accuracy: 98.76%
Unpermuted Accuracy: 99.48%Permuted Accuracy: 97.2%
Efficient recurrent architectures through activity sparsity and sparse back-propagation through time
Unpermuted Accuracy: 98.3%Permuted Accuracy: 95.1%
Unpermuted Accuracy: 99.63%Permuted Accuracy: 98.70%
Permuted Accuracy: 98.3%
Unpermuted Accuracy: 99%Permuted Accuracy: 96%
Permuted Accuracy: 97.83%
Unpermuted Accuracy: 99.1%Permuted Accuracy: 96.3%
Permuted Accuracy: 97.2%
Permuted Accuracy: 98.49%
Unpermuted Accuracy: 99%Permuted Accuracy: 95.4%
Permuted Accuracy: 96.8%
Permuted Accuracy: 96.94
Unpermuted Accuracy: 99.75Permuted Accuracy: 99.10