R2FP: Rich and robust feature pooling for mining visual data

• Main Authors: XIONG, Wei, DU, Bo, ZHANG, Lefei, HU, Ruimin, BIAN, Wei, SHEN, Jialie, TAO, Dacheng
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2015
• 主題: Autoencoder; Pooling; Representation learning; Computer Sciences; Databases and Information Systems
• 在線閱讀: https://ink.library.smu.edu.sg/sis_research/3539
• 機構: Singapore Management University

The human visual system proves smart in extracting both global and local features. Can we design a similar way for unsupervised feature learning? In this paper, we propose a novel pooling method within an unsupervised feature learning framework, named Rich and Robust Feature Pooling (R2FP), to bette...