AIMC Topic: Normal Distribution

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Effect of Subliminal Lexical Priming on the Subjective Perception of Images: A Machine Learning Approach.

PloS one
The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructe...

Multiple Kernel Point Set Registration.

IEEE transactions on medical imaging
The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue a...

Tracking Multiple Video Targets with an Improved GM-PHD Tracker.

Sensors (Basel, Switzerland)
Tracking multiple moving targets from a video plays an important role in many vision-based robotic applications. In this paper, we propose an improved Gaussian mixture probability hypothesis density (GM-PHD) tracker with weight penalization to effect...

Cough event classification by pretrained deep neural network.

BMC medical informatics and decision making
BACKGROUND: Cough is an essential symptom in respiratory diseases. In the measurement of cough severity, an accurate and objective cough monitor is expected by respiratory disease society. This paper aims to introduce a better performed algorithm, pr...

One pass learning for generalized classifier neural network.

Neural networks : the official journal of the International Neural Network Society
Generalized classifier neural network introduced as a kind of radial basis function neural network, uses gradient descent based optimized smoothing parameter value to provide efficient classification. However, optimization consumes quite a long time ...

Noise-enhanced convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generali...

A Fast Incremental Gaussian Mixture Model.

PloS one
This work builds upon previous efforts in online incremental learning, namely the Incremental Gaussian Mixture Network (IGMN). The IGMN is capable of learning from data streams in a single-pass by improving its model after analyzing each data point a...

Toward a General-Purpose Heterogeneous Ensemble for Pattern Classification.

Computational intelligence and neuroscience
We perform an extensive study of the performance of different classification approaches on twenty-five datasets (fourteen image datasets and eleven UCI data mining datasets). The aim is to find General-Purpose (GP) heterogeneous ensembles (requiring ...

Towards biological plausibility of electronic noses: A spiking neural network based approach for tea odour classification.

Neural networks : the official journal of the International Neural Network Society
The paper presents a novel encoding scheme for neuronal code generation for odour recognition using an electronic nose (EN). This scheme is based on channel encoding using multiple Gaussian receptive fields superimposed over the temporal EN responses...