A pure C++ neural network framework with zero deep-learning framework dependencies, featuring an interactive GUI for real-time MNIST handwritten digit recognition and AutoML hyperparameter search.

Abstract: Handwritten digit recognition is an important topic with applications ranging from digitizing historical documents to automating mailroom sorting. In recent years, there has been a rising ...

Abstract: Handwritten character recognition is a hot topic for research nowadays. If we can convert a handwritten piece of paper into a text-searchable document using the Optical Character Recognition ...

Agents use facial recognition, social media monitoring and other tech tools not only to identify undocumented immigrants but also to track protesters, current and former officials said. By Sheera ...

First, ensure you have the necessary tools installed on your computer. You’ll need Node.js and npm since they are required for CDK. Also, install Python 3.x and the ...

• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).

We found that, handwritten Bangla numerical character cannot be recognized using single machine learning algorithm or discrete wavelet transform (DWT). Above phenomenon motivated us to use combination ...