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Found 3 papers, 1 papers with code
Learning the Precise Feature for Cluster Assignment
Based on this, we propose a general-purpose deep clustering framework which radically integrates representation learning and clustering into a single pipeline for the first time.
Perception Driven Texture Generation
In this paper, we propose a joint deep network model that combines adversarial training and perceptual feature regression for texture generation, while only random noise and user-defined perceptual attributes are required as input.
A PCA-Based Convolutional Network
Particularly, each feature extraction stage includes two layers: a convolutional layer and a feature pooling layer.
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