Search results for "Cognition"

Why Cortices? Neural Networks for Visual Information Processing

1989

Neural networks for the processing of sensory information show remarkable similarities between different species and across different sensory modalities. As an example, cortical organization found in the mamalian neopallium and in the optic tecta of most vertebrates appears to be equally appropriate as a substrate for visual, auditory, and somatosensory information processing. In this paper, we formulate three structural principles of the vertebrate visual cortex that allow to analyze structure and function of these neural networks on an intermediate level of complexity. Computational applications are taken from the field of early vision. The proposed principles are: (a) Average anatomy, i …

Improving the Competency of Classifiers through Data Generation

2001

This paper describes a hybrid approach in which sub-symbolic neural networks and symbolic machine learning algorithms are grouped into an ensemble of classifiers. Initially each classifier determines which portion of the data it is most competent in. The competency information is used to generated new data that are used for further training and prediction. The application of this approach in a difficult to learn domain shows an increase in the predictive power, in terms of the accuracy and level of competency of both the ensemble and the component classifiers.

Clustering Quality and Topology Preservation in Fast Learning SOMs

2008

The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original …

Testing selected optimal descriptors with artificial neural networks

2013

Eleven properties have been modeled with the objective of checking the importance for model purposes of mixed descriptors made of empirical parameters, molecular connectivity indices and random numbers. The mixed descriptors with random indices have a descriptive character which is satisfactorily confirmed by the leave-one-out method of statistical analysis. The introduction of a partition of the set of compounds into training and evaluation sets decreases drastically the probability to find a mixed descriptor with random indices with good model quality. Two properties, the magnetic susceptibility and the elutropic values, insist on having optimal descriptors with random indices. The overal…

An Encrypted Traffic Classification Framework Based on Convolutional Neural Networks and Stacked Autoencoders

2020

In recent years, deep learning-based encrypted traffic classification has proven to be effective; especially, using neural networks to extract features from raw traffic to classify encrypted traffic. However, most of the neural networks need a fixed-sized input, so that the raw traffic need to be trimmed. This will cause the loss of some information; for example, we do not know the number of packets in a session. To solve these problems, a framework, which implements both a convolutional neural network (CNN) and a stacked autoencoder (SAE), is proposed in this paper. This framework uses a CNN to extract high-level features from raw network traffic and uses an SAE to encode the 26 statistica…

A Neural Architecture for 3D Segmentation

2003

An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.

Classification of Satellite Images with Regularized AdaBoosting of RBF Neural Networks

2008

Metacognition, Metalanguage and Metapragmatics

1993

Abstract In this article, the author briefly reports John Flavell's analysis of metacognition. By attempting to integrate metalinguistic activities into this analysis, the author brings to light several interesting characteristics of the field of meta-linguistics and its current state of research. Firstly, it appears that, unlike other meta-abilities, the metalinguistic abilities are defined in terms of their objects. On this basis, metalinguistic activities are at least partially independent of other metacognitive activities. Secondly, it appears that the position of metapragmatics in relation to meta-linguistics is in need of greater clarification. In particular, it seems necessary to dra…

Of course they do

2003

“With a little help from my friends”: Orthographic influences in spoken word recognition

2013

Resume Dans la presente etude, une tâche de decision lexicale auditive a ete utilisee avec des mots consistants (dans la direction phonie-graphie) ayant beaucoup, ou au contraire, peu « d’amis » au sein de leur voisinage phonologique. Les mots ayant beaucoup d’amis ont conduit a des temps de decision de lexicalite plus courts que ceux en ayant peu. Ce resultat est en accord avec l’hypothese selon laquelle l’orthographe faconne la perception des mots entendus du fait d’une restructuration des representations phonologiques par les connaissances orthographiques.