Yildirimhan Aydin computer vision

Overview

We developed a deep learning model using Convolutional Neural Networks (CNNs) to classify images from the CIFAR-10 dataset. The project utilized TensorFlow and Keras for building and training the model.

Achievements

• Achieved an accuracy rate of 85% on the test set.
• Implemented data augmentation techniques to improve model robustness …