IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK

April 2025
Vol-11, Issue-2
Paper ID: 26081
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Counterfeits Detection Convolutional Neural Networks MobileNet Support Vector Machines (SVM) Random Forest Hybrid Model Indian Currency Image Classification Machine Learning.
Abstract
The proliferation of counterfeit currency poses a significant threat to economic stability, necessitating advanced methods for effective detection. This project, titled "Identification of Fake Indian Currency Using Convolutional Neural Networks," proposes a novel approach to counterfeit detection by leveraging deep learning techniques. It explores several models, including MobileNet, a hybrid of MobileNet with Support Vector Machines (SVM), and a variant integrating MobileNet with both SVM and Random Forest, along with VGG16 and VGG19 architectures. MobileNet, known for its efficiency and accuracy in image classification, is evaluated for its ability to distinguish genuine Indian currency from counterfeit notes. The hybrid models aim to enhance detection capabilities by combining the strengths of MobileNet with traditional classifiers like SVM and Random Forest, using ensemble learning techniques to improve classification performance. These models are assessed based on accuracy, precision, recall, and overall robustness in real-world scenarios, with results highlighting the potential of convolutional neural networks to significantly improve counterfeit currency detection systems and strengthen financial security measures.

Author Information

# Name Institute / Affiliation
1 Pathuri Bharath Vasireddy Venkatadri Institute Of Technology
2 N.Durga Rao Vasireddy Venkatadri Institute Of Technology
3 Gopalam Lakshmi Sivannarayana Vasireddy Venkatadri Institute Of Technology
4 Bogolu venkata Ramanji Reddy Vasireddy Venkatadri Institute Of Technology
5 Ambati chaitanya krishna Vasireddy Venkatadri Institute Of Technology

How to Cite

Use the following formats to cite this article in your research.

APA Style
Bharath, Pathuri, Rao, N.Durga, Sivannarayana, Gopalam Lakshmi, Reddy, Bogolu venkata Ramanji, & krishna, Ambati chaitanya (2025). IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK. International Journal of Advance Research and Innovative Ideas In Education, 11(2), 1125-1133.
MLA Style
Bharath, Pathuri, et al. "IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, 2025, pp. 1125-1133.
IEEE Style
Pathuri Bharath, N.Durga Rao, Gopalam Lakshmi Sivannarayana, Bogolu venkata Ramanji Reddy, and Ambati chaitanya krishna, "IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, pp. 1125-1133, 2025.
Vancouver Style
Bharath Pathuri, Rao N.Durga, Sivannarayana Gopalam Lakshmi, Reddy Bogolu venkata Ramanji, krishna Ambati chaitanya. IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(2):1125-1133.
Harvard Style
Bharath, Pathuri, Rao, N.Durga, Sivannarayana, Gopalam Lakshmi, Reddy, Bogolu venkata Ramanji, & krishna, Ambati chaitanya (2025) 'IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK', International Journal of Advance Research and Innovative Ideas In Education, 11(2), pp. 1125-1133.
Chicago Style
Bharath, Pathuri, et al. "IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 1125-1133.
Turabian Style
Bharath, Pathuri, et al. "IDENTIFICATION OF FAKE INDIAN CURRENCY USING CONVOLUTIONAL NEURAL NETWORK." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 1125-1133.

Export Citation

Related Research

Design and Simulation of Boost Converter Using MOSFET and Diode in LTSpice
SWAPNIL SANJAY BAFANA 2026 ENGINEERING
PDF Unavailable
Smart Gesture-Based Home Security System using GSM Technology
Palak Ambule et al. 2026 Electronics & Communication Engineering
PDF Unavailable
Design and Performance Evaluation of a 2×2 Circular Microstrip Patch MIMO Antenna Array for Sub-6 GHz 5G Applications
M Manaswi et al. 2026 Electronics and Communication Engineering
PDF Unavailable
DESIGN AND PERFORMANCE ANALYSIS OF FREQUENCY RECONFIGURABLE PLANAR MONOPOLE ANTENNAS FOR WIRELESS APPLICATIONS
Dr.Chetan S et al. 2025 ELECTRONICS AND COMMUNICATION ENGINEERING
PDF Unavailable
BI-DIRECTIONAL WIRELESS CHARGING SYSTEM FOR EV
ABISHEK M et al. 2025 ELECTORNICE AND COMMUNICATION ENGINEERING
PDF Unavailable
Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks
Jayadevappa R.S et al. 2025 Electronics and Communication Engineering
PDF Unavailable