In this study, two modeling methods, namely response surface methodology (RSM) and artificial neural networks (ANN), were applied to investigate the Fenton process performance in landfill leachate treatment. For this purpose, three targets were used ...
IEEE transactions on pattern analysis and machine intelligence
Apr 6, 2017
Recognizing human actions from unknown and unseen (novel) views is a challenging problem. We propose a Robust Non-Linear Knowledge Transfer Model (R-NKTM) for human action recognition from novel views. The proposed R-NKTM is a deep fully-connected ne...
IEEE journal of biomedical and health informatics
Apr 6, 2017
Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neu...
Rare cell populations play a pivotal role in the initiation and progression of diseases such as cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to de...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Apr 5, 2017
In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230-300nm have been used for determination of antihistamine decongestant con...
Neural networks : the official journal of the International Neural Network Society
Apr 4, 2017
To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and co...
BACKGROUND: Current approaches to predict cardiovascular risk fail to identify many people who would benefit from preventive treatment, while others receive unnecessary intervention. Machine-learning offers opportunity to improve accuracy by exploiti...
In this paper, we propose a spiking neural network model for edge detection in images. The proposed model is biologically inspired by the mechanisms employed by natural vision systems, more specifically by the biologically fulfilled function of simpl...
Neural networks : the official journal of the International Neural Network Society
Apr 3, 2017
This work develops a generic framework, called the bag-of-paths (BoP), for link and network data analysis. The central idea is to assign a probability distribution on the set of all paths in a network. More precisely, a Gibbs-Boltzmann distribution i...
Journal of chemical information and modeling
Apr 3, 2017
We describe a new library generation method, Machine-based Identification of Molecules Inside Characterized Space (MIMICS), that generates sets of molecules inspired by a text-based input. MIMICS-generated libraries were found to preserve distributio...
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