zalandoresearch/fashion-mnist
A MNIST-like fashion product database. Benchmark :point_down:
PythonMIT
Issues
- 1
benchmark: Try HOG + SVM
#83 opened by sebadata - 1
AlexNet with Triplet loss Benchmark
#34 opened by cenkbircanoglu - 1
GoogleNet with Cross Entropy Benchmark
#33 opened by cenkbircanoglu - 10
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how to submit result?
#112 opened by styanddty - 8
DNN-for-fashion-mnist
#110 opened by Mengmengbai - 0
- 2
Shape of train images returns 55000 although it says 60000. Did I misunderstood smth?
#108 opened by moguzozcan - 0
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The gitter link in README shows as missing picture
#104 opened by akauppi - 4
Clustering performance
#96 opened by XifengGuo - 0
CoolNameNet - 94.7% accuracy with 295.968 params
#93 opened by edezhic - 0
Three Layer CNN With 90.33% accuracy
#91 opened by meghanabhange - 0
Benchmark: Conv Net - Accuracy: 90.26%
#87 opened by Abhi-H - 1
Loaders which use crop cause issue since difference in MNIST fashion and MNIST data in terms of pixels always black
#76 opened by thenamangoyal - 1
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Benchmarking
#74 opened by abelusha - 5
MNIST-Fashion-CNN
#73 opened by abelusha - 2
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arxiv-Broken link
#67 opened by karthikraobr - 1
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docs: Additional measure for benchmarking
#65 opened by AFAgarap - 2
ResNeXt (2017, Facebook AI Research)
#58 opened by taki0112 - 2
Benchmark: Conv Net - Accuracy: 92.56%
#59 opened by umbertogriffo - 7
Benchmark: 2 conv avg pool + 1 fc
#47 opened by rfratila - 0
VGG-like network with 26557k+ params ,93.5%
#48 opened by QuantumLiu - 2
benchmark: update on GRU+SVM with Dropout
#50 opened by AFAgarap - 1
Benchmark (MXNet gluon)
#28 opened by lianghong - 1
- 5
Plain 9 layers CNN for Benchmark
#41 opened by JMingKuo - 11
GRU+SVM+DROPOUT+LR-DECAY
#36 opened by mpekalski - 2
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Truncated Squeeze-net - a couple of runs
#39 opened by snakers4 - 3
3 Conv 2 FC layer Benchmark
#35 opened by cenkbircanoglu - 2
Is it possible to get the colored version?
#38 opened by pkern90 - 0
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benchmark: GRU+SVM for MNIST dataset
#30 opened by AFAgarap - 0
Adding Japanese README translation
#21 opened by hanxiao - 0
Benchmark: ResNet18 and Simple Conv Net
#25 opened by kefth - 0
[Suggestion] Point to `readMNIST` function from `darch` package to load fashion dataset
#17 opened by talegari - 3
Benchmark: Wide ResNet and DenseNets
#10 opened by ajbrock - 1
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