BDNet: Bengali handwritten numeral digit recognition based on densely connected convolutional neural networks
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Bengali handwritten digit recognition can be done using different image classification techniques. But the images of handwritten digits are different from natural images as the orientation of a digit as well as similarity of features of different digits are important. On the other hand, deep convolutional neural networks are achieving huge success in computer vision problems, especially in image classification. This BDNet is a densely connected deep convolutional neural network model based on state-of-the-art algorithm DenseNet to classify Bengali handwritten numeral digits. The BDNet has end-to-end trained using ISI Bengali handwritten numeral dataset with 5-fold cross-validation. The BDNet has achieved a test accuracy of 99.65 was 99.40 also gives 97.50 That is, this model gives a 41.66 state-of-the-art model. Codes, trained model and own dataset available at: https://github.com/Sufianlab/BDNet.
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