An improved palm vein recognition system using multimodal features and neural network classifier has been developed and presented in this paper. The effects of fusion of multiple features at various levels have been demonstrated. The shape and texture features have been considered for recognition of authenticated users and it is validated using neural network classifier. The recognition accurac...

defining maturity level is one of the important elements of the excellence models. this approach helps companies to assess competitive positions and help them to benchmark from best practices. one of the significant features of excellence models is defining maturity level using subjective and conventional approach. present research is a cross-sectional study among iranian petrochemical companie...

In this paper, we propose a bottom-up greedy and purely discriminative syntactic parsing approach that relies only on a few simple features. The core of the architecture is a simple neural network architecture, trained with an objective function similar to that of a Conditional Random Field. This parser leverages continuous word vector representations to model the conditional distributions of c...

Niels C. Haering Richard J. Qian M. Ibrahim Sezan University of Central Florida Sharp Labs of America Orlando, FL 32816 Camas, WA 98607 Abstract We propose a three-level algorithm to detect animal hunt events in wildlife documentaries. The rst level extracts texture, color and motion features, and detects motion blobs. The mid-level employs a neural network to verify the relevance of the detect...

Complex neuronal networks are an important tool to help explain paradoxical phenomena observed in biological recordings. Here we present a general approach to mathematically tackle a complex neuronal network so that we can fully understand the underlying mechanisms. Using a previously developed network model of the milk-ejection reflex in oxytocin cells, we show how we can reduce a complex mode...

In content-based image retrieval (CBIR), retrieval based on different features can be various by the way how to combine the feature values. Most of the existing approaches assume a linear relationship between different features, and the usefulness of such systems was limited due to the difficulty in representing high-level concepts using low-level features. In this paper, we introduce Neural Ne...

This study represents an innovative automatic method for black and white films colorization using texture features and a multilayer perceptron artificial neural network. In the proposed method, efforts are made to remove human interference in the process of colorization and replace it with an artificial neural network (ANN) which is trained using the features of the reference frame. Later, this...

This paper introduces a new channel selection strategy for reliable contentionaware data dissemination in multi-hop cognitive radio network. The key challenge here is to select channels providing a good tradeoff between connectivity and contention. In other words, channels with good opportunities for communication due to (1) low primary radio nodes (PRs) activities, and (2) limited contention o...

In this paper, we propose an intelligent and distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio network. Our strategy, SURF, classifies the available channels and uses them efficiently to increase data dissemination reliability in multi-hop cognitive radio networks. The classification is done on the basis of primary radio unoccupancy and of the ...