Skip to search formSkip to main contentSkip to account menu

Feature learning

Known as: Learning representation, Representation learning, Unsupervised feature learning 
In machine learning, feature learning or representation learning is a set of techniques that learn a feature: a transformation of raw data input to a… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
This paper advocates a novel learning solution to the modeling of long-term spatial-temporal saliency consistency in order to… 
Highly Cited
2016
Highly Cited
2016
We present a data-efficient representation learning approach to learn video representation with small amount of labeled data. We… 
Highly Cited
2016
Highly Cited
2016
In this work, we propose a semi-supervised method for short text clustering, where we represent texts as distributed vectors with… 
Highly Cited
2016
Highly Cited
2016
This letter proposes a simple but effective approach to automatically learn a multilayer image feature for satellite image scene… 
Highly Cited
2015
Highly Cited
2015
This paper presents a coupled discriminative feature learning (CDFL) method for heterogeneous face recognition (HFR). Different… 
Highly Cited
2015
Highly Cited
2015
Capturing user’s emotional state is an emerging way for implicit relevance feedback in information retrieval (IR). Recently, EEG… 
Highly Cited
2014
Highly Cited
2014
Recent advances in neural network training provide a way to efficiently learn representations from raw data. Good representations… 
2013
2013
This article presents a new global approach for detecting vanishing points and groups of mutually orthogonal vanishing directions… 
Highly Cited
1997
Highly Cited
1997
Much of the work on perception and understanding of music by computers has focused on low-level perceptual features such as pitch…