SFFAT Teachable Machine Model for Predictive Image Recognition

Sushavan Chatterjee; Ferdousi Pervin; Firdous SK; Anjana Das; Tanbir Ahammad Sekh

SFFAT Teachable Machine Model for Predictive Image Recognition

Authors: Sushavan Chatterjee, Ferdousi Pervin, Firdous SK, Anjana Das, Tanbir Ahammad Sekh

Unique Paper ID: 171709
Volume: 11
Issue: 8
PageNo: 818-819

Keywords: Image recognition Teachable Machine prediction model machine learning AI applications.

Abstract:
Image recognition has become an essential part of modern AI applications because of its impact on industries including healthcare, retail, and security. In this study, Google's SFFAT Teachable Machine is used to create a prediction model for image recognition. The article explains the fundamental concepts of the Teachable Machine, demonstrates how to construct a model for image recognition, and evaluates the machine's performance in prediction tasks. We show experimental results on a generated dataset and analyze the model's accuracy, usefulness, and potential for real-world applications.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 8
PageNo: 818-819

SFFAT Teachable Machine Model for Predictive Image Recognition

Available:https://ijirt.org/Article?manuscript=171709

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