Real-time digit recognition from user input Deep learning model built with TensorFlow Simple web interface using Flask Image preprocessing with Pillow and NumPy Draw a digit in the web interface or ...

Abstract: Handwritten digit recognition remains a pivotal area in machine learning and computer vision, essential for applications like license plate identification, form processing, and historical ...

This project focuses on classifying handwritten digits from the MNIST dataset using a Logistic Regression model. The MNIST dataset is a well-known benchmark in the field of machine learning, ...

Abstract: Handwritten digit recognition is assumed to be a huge part in numerous authentication applications in the state-of-art technologies. As the manually written digits are not always found in ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Multivariate statistical process monitoring (MSPM) methods have been widely used in ...

Acoustic hologram reconstructed results for the rotated target images of digit 4 which are used to evaluate the robustness of PhysNet-AH. The first row shows the diffracted acoustic field intensity ...

Since then, LeNet5 has served as a foundational model for the development of more advanced CNN architectures and has found applications in various domains, including character recognition, object ...

Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California 90089, United States ...