AIMC Topic: Neural Networks, Computer

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Approximate Bayesian MLP regularization for regression in the presence of noise.

Neural networks : the official journal of the International Neural Network Society
We present a novel regularization method for a multilayer perceptron (MLP) that learns a regression function in the presence of noise regardless of how smooth the function is. Unlike general MLP regularization methods assuming that a regression funct...

The effect of the neural activity on topological properties of growing neural networks.

Journal of integrative neuroscience
The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is conti...

Biomedical event trigger detection by dependency-based word embedding.

BMC medical genomics
BACKGROUND: In biomedical research, events revealing complex relations between entities play an important role. Biomedical event trigger identification has become a research hotspot since its important role in biomedical event extraction. Traditional...

The superior fault tolerance of artificial neural network training with a fault/noise injection-based genetic algorithm.

Protein & cell
Artificial neural networks (ANNs) are powerful computational tools that are designed to replicate the human brain and adopted to solve a variety of problems in many different fields. Fault tolerance (FT), an important property of ANNs, ensures their ...

Adaptive Online Sequential ELM for Concept Drift Tackling.

Computational intelligence and neuroscience
A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM...

Cognitive Offloading Does Not Prevent but Rather Promotes Cognitive Development.

PloS one
We investigate the relation between the development of reactive and cognitive capabilities. In particular we investigate whether the development of reactive capabilities prevents or promotes the development of cognitive capabilities in a population o...

Stability analysis for uncertain switched neural networks with time-varying delay.

Neural networks : the official journal of the International Neural Network Society
In this paper, stability for a class of uncertain switched neural networks with time-varying delay is investigated. By exploring the mode-dependent properties of each subsystem, all the subsystems are categorized into stable and unstable ones. Based ...

Event Recognition Based on Deep Learning in Chinese Texts.

PloS one
Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features u...

Deep learning based classification of breast tumors with shear-wave elastography.

Ultrasonics
This study aims to build a deep learning (DL) architecture for automated extraction of learned-from-data image features from the shear-wave elastography (SWE), and to evaluate the DL architecture in differentiation between benign and malignant breast...

Prediction of fermentation index of cocoa beans (Theobroma cacao L.) based on color measurement and artificial neural networks.

Talanta
Several procedures are currently used to assess fermentation index (FI) of cocoa beans (Theobroma cacao L.) for quality control. However, all of them present several drawbacks. The aim of the present work was to develop and validate a simple image ba...