Neural networks enhance image recognition accuracy through deep learning techniques that enable the model to learn from vast datasets. They automatically extract features, such as edges and shapes, without explicit programming. As they process images through multiple layers, they improve their ability to identify patterns and classify objects more effectively. The more data they are trained on, the better their performance becomes, allowing for improved object detection and facial recognition capabilities. As a result, neural networks are pivotal in applications ranging from medical imaging to autonomous vehicles.