[PDF] Top 20 Classification of color textures with random field models and neural networks
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Classification of color textures with random field models and neural networks
... examples of color texture classification or the involvement of Neural Networks in such task are the works presented in [1], [2], [3], and ...pure color vectors as ... See full document
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Butterfly Classification by HSI and RGB Color Models Using Neural Networks
... the classification of Butterfly species through the implementation of Neural Networks and Image ...total of 9 species of Morpho genre which has blue as a ... See full document
11
Design and implementation of computational models for film assessment and classification
... area and improving every business. The intuition of knowledgeable veterans has been changed by the accu- racy of trained ...while, and the new step in the evolution is being as disruptive as ... See full document
66
Artificial neural networks applied to the resolution of regression and classification multivariate analysis problems in the agricultural and the industrial fields
... mathematical models of processes to predict the unknown value of a process variable as a function of known values of variables of this ...Mathematical models have been ... See full document
133
Acceleration of a bacterial metabolic simulation using neural networks with optimization techniques
... Intelligence and opti- mization methods to approximate a biological calculation such as the metabolism of cells, understanding metabolism as the different internal chemical reactions of a cell that ... See full document
116
Data Mining with Enhanced Neural Networks-CMMSE
... behavior of the weights of the network, for a first data set defining a function ...collection of values that define a functional relationship ...relationship and the output pattern of ... See full document
16
Heterogeneous neural networks: theory and applications
... The basic measure was then enhanced allowing fuzzy sets (in the form of fuzzy numbers) to occur as part of the input and the corresponding weights. The resulting generic model of which [r] ... See full document
320
Ensembles of Artificial Neural Networks: Analysis and Development of Design Methods
... case of 3 networks in the ...medium and high sized ensembles (typically 20 and 40 networks in the ensemble) and it provides the best overall results of these ...results ... See full document
415
Facial action unit detection with convolutional neural networks
... convolutional neural network architecture to study the problem of action unit ...task of predicting the presence of a specific action unit in a still image as simple image-level binary ... See full document
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Color image segmentation using multispectral random field texture model & color content features
... performance of the proposed segmentation algorithm and the associated features is illustrated in ...4 and 5. Fig. 4 shows five images each containing a number of different ...form of a ... See full document
6
Regression models with MoPs Bayesian networks
... extension of Zong (2006); Zong and Lam (1998), for the estimation of multivariate densities with B-spline, in particular, given knots sequences and orders for each dimension, the ... See full document
10
Entropy characterization of random network models
... P and, given a (sample) network and a set s of chosen features (number of links, number of triangles, ...likelihood of the sample network and all networks ... See full document
13
Distant galaxies analysis with deep neural networks
... • Design and training of 4 different neural networks • Prediction of Redshift, Stellarity, Stellar Mass and Spectral Type of galaxies • Data from Alhambra Survey • Comparison of Predicte[r] ... See full document
31
Forecasting of time series with trend and seasonal cycle using the airline model and artificial neural networks
... Diferentes ideas han sido planteadas en la literatura para obtener nuevos modelos no lineales, basados en redes neuronales artificiales, que usan como informaci´ on de entrada las observ[r] ... See full document
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TítuloComputational models of neuron astrocyte interactions lead to improved efficacy in the performance of neural networks
... behavior of the nervous system (NS) remains a mystery in many ...details of how the brain performs certain information processing tasks, such as classification, pattern recognition, and ... See full document
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TítuloMIANN models of networks of biochemical reactions, ecosystems, and U S Supreme Court with Balaban Markov indices
... combination of J with the first-order Randic connectivity index 1 χ improved the results ...index and the electro- topological index for the prediction of retention data of ... See full document
18
Fair coexistence of scheduled and random access wireless networks: unlicensed LTE/WiFi
... presence of unlicensed LTE networks may degrade the performance of existing ...details of the coexistence mech- anisms used are not ...Qualcomm and Huawei have presented their own white ... See full document
14
Categorical Missing Data Imputation Using Fuzzy Neural Networks with Numerical and Categorical Inputs
... enough, and missing values have to be ...potential of using methods to automatically obtain fuzzy set membership ...using neural networks. In this work a new fuzzy min-max neural ... See full document
10
Assisting the training of deep neural networks with applications to computer vision
... plenty of theoretical and empirical evidence on the impact of depth in neural network’s performance [17, 18, 144, ...training of a network more difficult. Despite the numerous efforts ... See full document
151
On Exponential Periodicity And Stability of Nonlinear Neural Networks With Variable Coefficients And Distributed Delays
... use of constant fixed delays in models of delayed feedback provides of a good approx- imation in simple circuits consisting of a small number of ...However, neural ... See full document
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