Saliency Map Classification Using Capsule-based CNNs

Saliency Map Classification Using Capsule-based CNNs is a scholarly work, published in 2018 in ''Journal of Vision''. The main subjects of the publication include convolutional neural network, artificial intelligence, computer vision, eye tracking, fixation, pattern recognition, and computer science. Results show that CapsuleNets improve accuracy rates and minimize loss for saliency map classification by up to 35% compared to traditional CNNs.