Development an Accurate Neural Network for Coin Recognition

Fonov, Nikolay; Urkaeva, Ksenia

doi:10.1109/elconrus51938.2021.9396592

Cited by 4 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another successful research with an accuracy of 98.71% is by development of an accurate neural network for coin recognition in 2021, which uses Russian coins [16]. Another recent study that explores all classification technique is from [17] in 2021. They studied two different types of feature extraction, gray-level cooccurrence matrix (GLCM) and histogram-oriented gradients (HOG), and trained them using six various classification technique.…”

Section: Overview Of Machine Learningmentioning

confidence: 99%

Malaysia coin identification app using deep learning model

et al. 2023

View full text Add to dashboard Cite

Most of the human work has been replaced by computers in recent years. With the rise of mobile technology and Internet access, recent developments in machine learning (ML) have designed many algorithms to solve diverse human problems. However, due to a lack of exposure to image processing, identification technology is still not widely employed in Malaysia. This paper outlines the steps involved in creating a mobile application for coin identification using ML. In the literature review, the history of the coins is studied in more depth and the features of already existing coin identification mobile applications are compared by their advantages and disadvantages. In addition, using the neural network model, the classification accuracy of successfully identified coins is recorded and disclosed. This study includes the limitations of the prototype mobile application and future improvements that could be added.

show abstract

Section: Overview Of Machine Learningmentioning

confidence: 99%