Image segmentation techniques: statistical, comprehensive, semi-automated analysis and an application perspective analysis of mathematical expressions
Segmentation has been a rooted area of research having diverse dimensions. The roots of
image segmentation and its associated techniques have supported computer vision, pattern …
image segmentation and its associated techniques have supported computer vision, pattern …
A retrospective study on handwritten mathematical symbols and expressions: Classification and recognition
V Kukreja - Engineering Applications of Artificial Intelligence, 2021 - Elsevier
Context: Many scientific and technical literature documents contain MSs and MEs that are
more challenging to be recognized by computers than plain text. The recognition of HMSE …
more challenging to be recognized by computers than plain text. The recognition of HMSE …
Machine learning models for mathematical symbol recognition: A stem to stern literature analysis
Given the ubiquity of handwriting and mathematical content in human transactions, machine
recognition of handwritten mathematical text and symbols has become a domain of great …
recognition of handwritten mathematical text and symbols has become a domain of great …
Machine learning and non-machine learning methods in mathematical recognition systems: Two decades' systematic literature review
Tools based on machine learning (ML) have seen widespread application in the prediction
and categorization of mathematical symbols and phrases. The purpose of this work is to …
and categorization of mathematical symbols and phrases. The purpose of this work is to …
A dive in white and grey shades of ML and non-ML literature: a multivocal analysis of mathematical expressions
With the advent and advancement of machine learning and deep learning techniques,
machine-based recognition systems for mathematical text have captivated the attention of …
machine-based recognition systems for mathematical text have captivated the attention of …
Recognition of simple handwritten polynomials using segmentation with fractional calculus and convolutional neural networks
FCF Marques, TP De Araujo, CC Nator… - 2019 8th Brazilian …, 2019 - ieeexplore.ieee.org
This work introduces a method for recognizing handwritten polynomials using Convolutional
Neural Networks (CNN) and Fractional Order Darwinian Particle Swarm Optimization …
Neural Networks (CNN) and Fractional Order Darwinian Particle Swarm Optimization …
Cnn-based handwritten mathematical symbol recognition model
Mathematical expression or formula recognition system is evolving field in pattern
recognition. Various methods are implemented by different researchers on wide areas …
recognition. Various methods are implemented by different researchers on wide areas …
Machine learning tensor flow based platform for recognition of hand written text
N Gupta, N Goyal - 2021 International Conference on Computer …, 2021 - ieeexplore.ieee.org
Handwritten text recognition in a computer is an automatic mode that transcribe documents.
Mainly two types of approaches are used in handwritten text recognition are artificial neural …
Mainly two types of approaches are used in handwritten text recognition are artificial neural …
Multi‐Lingual Handwritten Character Recognition Using Deep Learning
G Parihar, R Rajalakshmi… - … Analysis and Deep …, 2021 - Wiley Online Library
Handwritten character recognition (HCR) is the most challenging task because it is a
repeated work which is done by humans, and because of that, error can occur. We can solve …
repeated work which is done by humans, and because of that, error can occur. We can solve …
Handwritten mathematical recognition tool
M Abirami, S Jaganathan - 2019 International Conference on …, 2019 - ieeexplore.ieee.org
The recognition of handwritten mathematical expressions has received an increasing
amount of attention in pattern recognition research. It is the process of taking in raw data and …
amount of attention in pattern recognition research. It is the process of taking in raw data and …