Unsupervised Image Classification Using Multi-Autoencoder and K-means++
Shingo Mabu, Kyoichiro Kobayashi, Masanao Obayashi, Takashi Kuremoto · Journal of Robotics Networking and Artificial Life · 2018
Supervised learning algorithms such as deep neural networks have been actively applied to various problems.However, in image classification problem, for example, supervised learning needs a large number of data with correct labels.In fact, the cost of giving correct labels to the training data is large; therefore, this paper proposes an unsupervised image classification system with Multi-Autoencoder and K-means++ and evaluates its performance using benchmark image datasets.