Results 71 to 80 of about 2,516,559 (186)

Clustering Based Feature Learning on Variable Stars

, 2016
The success of automatic classification of variable stars strongly depends on the lightcurve representation. Usually, lightcurves are represented as a vector of many statistical descriptors designed by astronomers called features.
Mackenzie, Cristóbal, Pichara, Karim, Protopapas, Pavlos   +2 more
core   +1 more source

Feature and Region Selection for Visual Learning

, 2016
Visual learning problems such as object classification and action recognition are typically approached using extensions of the popular bag-of-words (BoW) model.
Cabral, Ricardo, De la Torre, Fernando, Wang, Liantao, Zhao, Ji   +3 more
core   +2 more sources

Video Tracking Using Learned Hierarchical Features [PDF]

IEEE Transactions on Image Processing, 2015
In this paper, we propose an approach to learn hierarchical features for visual object tracking. First, we offline learn features robust to diverse motion patterns from auxiliary video sequences. The hierarchical features are learned via a two-layer convolutional neural network.
Wang, Gang, Chan, Kap Luk, Liu, Ting, Yang, Qingxiong, Wang, Li   +4 more
openaire   +3 more sources

Feature Reinforcement Learning in Practice [PDF]

, 2012
Following a recent surge in using history-based methods for resolving perceptual aliasing in reinforcement learning, we introduce an algorithm based on the feature reinforcement learning framework called PhiMDP. To create a practical algorithm we devise a stochastic search procedure for a class of context trees based on parallel tempering and a ...
Nguyen, Phuong, Sunehag, Peter, Hutter, Marcus   +2 more
openaire   +3 more sources

Learning From the Features We Ignore: A Critical Perspective on Feature Engineering and the Role of Feature Learning in Learning Analytics

IEEE Access
The integration of machine learning within educational environments has positioned learning analytics as a valuable approach for enhancing teaching and learning outcomes.
Dino Vlahek, Dijana Oreski, Marija Pokos Lukinec   +2 more
doaj   +1 more source

Long-Tailed Learning Requires Feature Learning

, 2022
We propose a simple data model inspired from natural data such as text or images, and use it to study the importance of learning features in order to achieve good generalization. Our data model follows a long-tailed distribution in the sense that some rare subcategories have few representatives in the training set.
Laurent, Thomas, von Brecht, James H., Bresson, Xavier   +2 more
openaire   +2 more sources

Enhanced visibility graph for EEG classification

Frontiers in Neuroscience
Electroencephalography (EEG) holds immense potential for decoding complex brain patterns associated with cognitive states and neurological conditions. In this paper, we propose an end-to-end framework for EEG classification that integrates power spectral
Asma Belhadi, Pedro G. Lind, Pedro G. Lind, Pedro G. Lind, Youcef Djenouri, Youcef Djenouri, Anis Yazidi, Anis Yazidi   +7 more
doaj   +1 more source

Learning to Learn Kernels with Variational Random Features

Proceedings of Machine Learning Research, 2020
ICML'2020; code is available in: https://github.com/Yingjun-Du ...
Zhen, X., Sun, H., Du, Y., Xu, J., Yin, Y., Shao, L., Snoek, C.   +6 more
openaire   +3 more sources

IGSMNet: Ingredient-Guided Semantic Modeling Network for Food Nutrition Estimation

Foods
In recent years, food nutrition estimation has received growing attention due to its critical role in dietary analysis and public health. Traditional nutrition assessment methods often rely on manual measurements and expert knowledge, which are time ...
Donglin Zhang, Weixiang Shi, Boyuan Ma, Weiqing Min, Xiao-Jun Wu   +4 more
doaj   +1 more source

Multi-Labeled Recognition of Distribution System Conditions by a Waveform Feature Learning Model

Energies, 2019
A waveform contains recognizable feature patterns. To extract the features of various equipment disturbance conditions from a waveform, this paper presents a practical model to estimate distribution line (DL) conditions by means of a multi-label extreme ...
Sang-Keun Moon, Jin-O Kim, Charles Kim
doaj   +1 more source