Read previous issues. You need to log in to edit. You can create a new account if you don't have one. Or, discuss a change on Slack. Full name optional :. Homepage URL optional :. Paper where the dataset was introduced: Introduction date:. Dataset license:. URL to full license terms:. Image Currently. Supported frameworks: TensorFlow. Add or remove modalities: Images.
Add or remove languages:. Higher is better for the metric. Uses extra training data. Data evaluated on. SVHN has three sets: training, testing sets and an extra set with images that are less difficult and can be used for helping with the training process Source: Competitive Multi-scale Convolution.
Benchmarks Edit Add a new result Link an existing benchmark. Semi-Supervised Image Classification. Meta Pseudo Labels. Domain Adaptation. SVHN is a real-world image dataset for developing machine learning and object recognition algorithm.
The model attempts to do both detection using bouding-box regressiong and digit-wise classification of numbers in the dataset using 2 CNNs. I modified the original SVHN datasset to make it readily workable with keras. The modified dataset contains original train and test images, cropped to bounding box train and test images and two CSV files containing all the information about bounding boxes and labels of train and test images.
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