AIMC Topic: Algorithms

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Deep neural networks for texture classification-A theoretical analysis.

Neural networks : the official journal of the International Neural Network Society
We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive the size of the feature space f...

Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals.

Computational intelligence and neuroscience
Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlie...

Consensus Kernel -Means Clustering for Incomplete Multiview Data.

Computational intelligence and neuroscience
Multiview clustering aims to improve clustering performance through optimal integration of information from multiple views. Though demonstrating promising performance in various applications, existing multiview clustering algorithms cannot effectivel...

Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.

Neural networks : the official journal of the International Neural Network Society
A novel, unsupervised nonparametric model of multivariate probability density functions (pdf) is introduced, namely the Parzen neural network (PNN). The PNN is intended to overcome the major limitations of traditional (either statistical or neural) p...

Melanoma segmentation based on deep learning.

Computer assisted surgery (Abingdon, England)
Malignant melanoma is one of the most deadly forms of skin cancer, which is one of the world's fastest-growing cancers. Early diagnosis and treatment is critical. In this study, a neural network structure is utilized to construct a broad and accurate...

The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation.

Implementation science : IS
BACKGROUND: Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evid...

Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.

Computational and mathematical methods in medicine
Body constitution classification is the basis and core content of traditional Chinese medicine constitution research. It is to extract the relevant laws from the complex constitution phenomenon and finally build the constitution classification system...

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

Drug development and industrial pharmacy
This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was...

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

Molecules (Basel, Switzerland)
With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological...

Error-Correcting Factorization.

IEEE transactions on pattern analysis and machine intelligence
Error Correcting Output Codes (ECOC) is a successful technique in multi-class classification, which is a core problem in Pattern Recognition and Machine Learning. A major advantage of ECOC over other methods is that the multi-class problem is decoupl...