Examples of Tensorflow Lite on Android
-
Updated
Aug 19, 2026 - Kotlin
Examples of Tensorflow Lite on Android
It is a Python GUI in which you can draw a digit and the ML Algorithm will recognize what digit it is. We have used Mnist dataset
Sample android application to detect digit drawn using TensorFlow & Firebase model.
This project implements a CNN for handwritten digit classification on the MNIST dataset using PyTorch. It uses stacked convolutional layers with dropout, batch normalization, and max pooling to classify 28×28 grayscale digits (0–9) with Softmax output.
Neuromorphic Spiking Neural Network (SNN) digit classifier built using PyTorch, snnTorch, and Streamlit. Simulates Leaky Integrate-and-Fire (LIF) neuron dynamics with interactive canvas drawing and real-time spike raster plots.
This is a machine learning project focused on accurately classifying handwritten digits from the popular MNIST dataset. It provides a collection of code and models that leverage different techniques to achieve high accuracy in recognizing and categorizing digits.
MNIST Digit Recognition Using Scikit-Learn and Ensemble Learning and Then Make an Web-App Using Flask.
A handwritten digit classifier application with python, java, klotin and tensorflow dependencies
This research aims to enhance the performance of LBP-based convolutional neural networks on the automatic recognition of bilingual handwriting.
FPGA-based TPU-style accelerator for handwritten digit classification. Implements a fully pipelined INT8 neural network on a Cyclone II FPGA, using a weight-stationary systolic MAC array to classify 16×16 MNIST digits in ~9.4 µs of pure compute time, with UART input and VGA output.
MATLAB digit classifier based on Andrew NG course
A simple digit classifier built using the MNIST dataset
An implementation of multiclass perceptron as a digit recognizer
This project encompasses a series of modules designed to facilitate the creation, training, and prediction using a PyTorch MLP Neural Network for digit classification based on the MNIST dataset.
Machine learner to classify a single handwritten digit on an image.
Deep Learning project with MNIST dataset to help machines recognizing handwritten digits
2nd Project of Course 'Machine Learning' of the SMARTNET programme. Taken at the National and Kapodistrian University of Athens.
Training different models to solve the MNIST digit dataset
To associate your repository with the digit-classifier topic, visit your repo's landing page and select "manage topics."