Performance of trained neural networks on noisy data sets
Knowledge Extraction From Trained Neural Networks
... Artificial neural networks (ANN) are very efficient in solving various kinds of problems But Lack of explanation capability (Black box nature of Neural Networks) is one of the most important ...
Instantaneously trained neural networks with complex and quaternion inputs
... Abstract Neural network architectures such as backpropagation networks, perceptrons or generalized Hopfield networks can handle complex inputs but they require a large amount of time and resources ...
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Harnessing Pre Trained Neural Networks with Rules for Formality Style Transfer
... Bi-directional FT † 70.61 3.98 72.01 41.74 GPT-CAT 71.45 3.81 72.70 44.07 Table 3: Test performance on the E&M domain. PINC reflects the dissimilarity to the original informal sen- tence. Neither a too high nor a ...
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Decision Rule Extraction from Trained Neural Networks Using Rough Sets
... the trained neural ...rough sets; Section 4 describes our new method for rule extraction; Section 5 contains a experimental comparison using two data sets for the two symbolic mapping ...
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Noisy training for deep neural networks in speech recognition
... when trained with an appropriate objective function, and it is a hierarchical model that can learn patterns of speech signals from primitive levels to high ...miserable performance reduction if the training ...
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Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks
... 2013 ; Avermann et al. 2012 ; Lefort et al. 2009 ), (Fig. 1 B). PV neurons are modeled here to receive inhibition from both PV and Sst neurons, whereas Sst neurons only receive exci- tatory input (Pfeffer et al. 2013 ; ...
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Classification of small data sets of images with transfer learning in convolutional neural networks
... speed. Neural networks are in a big expansion in a new ...Convolutional neural networks have been widely applied to a variety of pattern recognition problems, such as computer ...convolutional ...
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Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure
... ImageNet data set to achieve performance comparable to our baseline ...on performance, any comparison confounds architecture and ...we trained small instances of both architectures on just ...
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Challenging the Efficient Market Hypothesis with Dynamically Trained Artificial Neural Networks
... weekly data, however, does not support using a longer-term training history with ...training sets is more detrimental to accuracy/hit rate than are the informational limitations of shorter, more current ...
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Ensemble neural networks using interval neutrosophic sets and bagging
... three data sets named ionosphere, pima, and liver from UCI Machine Learning Repository are applied to our ...Each data set is split into a training set and a testing ...both sets are shown in ...
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NEURAL NETWORKS IN DATA MINING
... 39 Neural networks essentially comprise three pieces: the architecture or model; the learning algorithm; and the activation ...functions. Neural networks are programmed or “trained” to ...
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Creep modelling of polypropylenes using artificial neural networks trained with Bee algorithms
... of data modelling in which the collection of data are used to develop a model so that details of unknown aspects/states of the particular problem under consideration to be ...and trained with ...
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3D Ground Truth Generation Using Pre-Trained Deep Neural Networks
... deep networks to distill complex patterns from noisy ...human performance in image ...improving performance for autonomous driving related tasks, and has led to robust progress in diverse ...
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License Plate Recognition using Convolutional Neural Networks Trained on Synthetic Images
... test sets in section ...and trained models that work out of the box with the LPR pipeline without further calibration in section ...the performance on the Italian data set we created in ...
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Neural nets their use and abuse for small data sets
... a neural network, as suggested by Borggaard (1995), will obviously reduce this difficulty, but there is still a need for more powerful visualisation ...the neural net models failed to match the predictive ...
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Boosting Information Extraction Systems with Character level Neural Networks and Free Noisy Supervision
... deep neural net- works to leverage large amounts of data to learn complex ...is trained using a measure of consis- tency between extracted data and existing databases as a form of cheap, ...
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Applications of Artificial Neural Networks to Synthetic Aperture Radar for Feature Extraction in Noisy Environments
... before data is ...Artificial Neural Networks, as well as some methodology in images ...of data, trials and testing sets can be found in the appendices along with the used MATLAB ...
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Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks
... Chapter 3 Supply File Due to the differences between the SDNN and SNN, the conversion program creates a supply file along with a converted network file from every original SDNN. The network file is straightforward: Is ...
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Data Driven Computing with Noisy Material Data Sets
... the data driven solution relative to the reference solution as a function of λ and data set ...increasing data set ...the data driven solution relative to the reference solution as a function ...
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A Stochastic Max Pooling Strategy for Convolutional Neural Network Trained by Noisy Samples
... convolutional neural network (CNN) has made remarkable progress in image classifica- ...extracting noisy image ...classified noisy images much more accurately than traditional pooling ...
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