Residual Squeeze VGG16

Understand

Deep learning has given way to a new era of machine learning, apart from computer vision.

• Convolutional neural networks have been implemented in image classification, segmentation and object detection.
• Despite recent advancements, we are still in the very early stages and have yet to settle on best practices for network architecture in terms of deep design, small in size and a short training time.
• In this work, we propose a very deep neural network comprised of 16 Convolutional layers compressed with the Fire Module adapted from the SQUEEZENET model.