Currency Classification Using Deep Learning

Currency Classification Using Deep Learning

         K. Amrutha Jyothsna, Mrs.A.Sirisha(Assist.Professsor)

MCA Student, Department of Master of Computer Applications,

Vignan’s Institute of Information Technology(A),

 Beside VSEZ,Duvvada,Vadlapudi Post, Gajuwaka,

 Visakhapatnam-530049.

Assistant Professor, Department of Information Technology,

          Vignan’s Institute of Information Technology(A), Beside VSEZ,Duvvada,Vadlapudi Post,

ABSTRACT

Among the uses of machine learning is the recognition of facial expressions. Based on the features that are derived from an image, it assigns a facial expression to one of the classes of facial expressions. Convolutional Neural Network (CNN) is a classification technique that may also be used to identify patterns in an image. We used the CNN approach to identify facial expressions in our proposed study. To increase the precision of facial emotion recognition, the wavelet transform is used after CNN processing. Seven distinct facial expressions are included in the facial expression image dataset that was obtained from Kaggle. The findings of the face expression recognition experiment utilizing CNN and wavelet transform show that the accuracy is improved, and the output is audible.
Index Terms: Facial and Convolutional Neural Nets