Simple, reliable seven-segment OCR using OpenCV

In this part, we developed an interface for Digit Classification using the PyQt5 library in Python.

This project uses an esp32 camera to take pictures of an analogue gas meter. A tflite model detects the position of the dial which is cut out, sliced and then a simple CNN model classifies the numbers one by one.

A complete, straightforward digit classification project built with PyTorch, featuring CNN-based training, evaluation metrics, confusion matrix visualization, and XAI using Grad-CAM.

A Simple MNIST Digit Classifier Neural Network that recognises hand-written numerical digits from the MNIST Digit Recogniser Dataset made from scratch* in Python with 7960 trainable parameters...

Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) implementation on different datasets for classification in Machine Learning.

This project utilizes logistic regression to classify numbers 0 and 1 using sign language gestures. It successfully achieves the task of sign language classification, reaching a test accuracy of 93.54%.

Tensorflow2, working on Mnist and GTSRB

A simple C++ program to classify a user-entered number as positive, negative, or zero, demonstrating basic C++ syntax and operations.

This project is designed to classify handwritten digits (0-9) using a neural network built with TensorFlow and Keras.

A public API for HNG Stage 1 task that classifies a given number by identifying its mathematical properties (prime, perfect, Armstrong, parity, digit sum) and retrieves a fun fact using the Numbers API.