Abstract In this essay, we explore machine learning (ML) and deep learning (DL) techniques for handwritten mathematical symbol recognition. Using a dataset of over 10,000 images across 19 classes, we ...

This project focuses on handwritten mathematical symbol recognition and classification using machine learning models. It involves developing models that can accurately recognize and categorize ...

This paper describes an approach for offline recognition of handwritten mathematical symbols. The process of symbol recognition in this paper includes symbol segmentation and accurate classification ...

It enables them to understand intricate mathematical equations, symbols, and declarations. Still, there are many challenges in accurately identifying NBMC. This makes it more difficult for those with ...

How much math knowledge do you need for machine learning and deep learning? Some people say not much. Others say a lot. Both are correct, depending on what you want to achieve.

Deep learning is rapidly ‘eating’ artificial intelligence. But let's not mistake this ascendant form of artificial intelligence for anything more than it really is. The famous author Arthur C ...

Satellite signal symbol rate estimation is an important problem in spectrum sensing. Once the symbol rate is known, the received signal can be re-sampled to match the symbol rate. Thus accurate symbol ...