Powerpoint Convolution Neural Networks (CNNs)

Powerpoint Convolution Neural Networks (CNNs)

1. Convolution Neural Networks (CNNs ) By PRATHEESH KUMAR N

2. Convolution plays a key role in convolutional neural networks (CNNs).  CNNs are a type of deep network commonly used to analyze images.  CNNs eliminate the need for manual feature extraction, which is why they work very well for complex problems such as image classification and medical image analysis . CNNs are effective for non-image data analysis such as audio, time-series, and signal data.

3. CNNs have several layers, the most common of which are convolution, ReLu , and pooling.

4. Layers in a convolutional neural network (CNN ) Convolution layers act as filters—each layer applies a filter and extracts specific features from the image . These filter values are learned by the network when the network is trained . The initial layers typically extract low-level features while the deeper layers extract high-level features from the data .