Deep Convolutional Decision Jungle for Image Classification

Understand

We propose a novel method called deep convolutional decision jungle (CDJ) and its learning algorithm for image classification.

• The CDJ maintains the structure of standard convolutional neural networks (CNNs), i.e.
• multiple layers of multiple response maps fully connected.
• Each response map-or node-in both the convolutional and fully-connected layers selectively respond to class labels s.t.