SVHN街景门牌号数据集

SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting. It can be seen as similar in flavor toMNIST(e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over 600,000 digit images) and comes from a significantly harder, unsolved, real world problem (recognizing digits and numbers in natural scene images). SVHN is obtained from house numbers in Google Street View images.ReferencePlease cite the following reference in papers using this dataset:Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, Andrew Y. NgReading Digits in Natural Images with Unsupervised Feature LearningNIPS Workshop on Deep Learning and Unsupervised Feature Learning 2011. (PDF)Please usehttp://ufldl.stanford.edu/housenumbersas the URL for this site when necessaryFor questions regarding the dataset, please [e-mail]