This work presents the Transition-Aware Human Activity Recognition (TAHAR) system architecture for the recognition of physical activities using smartphones. It targets real-time c...
Jorge Luis Reyes-Ortiz, Luca Oneto, Albert Sam&agr...
In this paper, we propose a novel latent structural model for big data image recognition. It addresses the problem that large amount of labeled training samples are needed in trad...
Lei Liu, Xiao Bai 0001, Huigang Zhang, Jun Zhou, W...
Pairwise clustering methods partition a dataset using pairwise similarity between data-points. The pairwise similarity matrix can be used to define a Markov random walk on the da...
Due to dynamic and uncertain nature of many optimization problems in real-world, an algorithm for applying to this environment must be able to track the changing optima over the t...
Babak Nasiri, Mohammad Reza Meybodi, Mohammad Mehd...
Extreme Learning Machine (ELM), which was initially proposed for training single-layer feed-forward networks (SLFNs), provides us a unified efficient and effective framework for...
A demand for predictive models for on-line estimation of variables is increasing in industry. As industrial processes are timevarying, on-line learning algorithms should be adapti...
l Abstract A Novel Motion Classification Based Intermode Selection Strategy for HEVC Performance Improvement Pallab Kanti Podder1 , Manoranjan Paul1 and Manzur Murshed2 1 School of...
Pallab Kanti Podder, Manoranjan Paul, M. Manzur Mu...
Hidden Markov models (HMMs) are widely used probabilistic models of sequential data. As with other probabilistic models, they require the specification of local conditional proba...
The Virtual Generalizing Random Access Memory Weightless Neural Network (VGRAM WNN) is a type of WNN that only requires storage capacity proportional to the training set. As such,...
Avelino Forechi, Alberto F. De Souza, Jorcy de Oli...