Search results for "image processing"
showing 10 items of 3285 documents
Face Inpainting via Nested Generative Adversarial Networks
2019
Face inpainting aims to repaired damaged images caused by occlusion or cover. In recent years, deep learning based approaches have shown promising results for the challenging task of image inpainting. However, there are still limitation in reconstructing reasonable structures because of over-smoothed and/or blurred results. The distorted structures or blurred textures are inconsistent with surrounding areas and require further post-processing to blend the results. In this paper, we present a novel generative model-based approach, which consisted by nested two Generative Adversarial Networks (GAN), the sub-confrontation GAN in generator and parent-confrontation GAN. The sub-confrontation GAN…
Multilevel assessment of mental stress via network physiology paradigm using consumer wearable devices
2019
Mental stress is a physiological condition that has a strong negative impact on the quality of life, affecting both the physical and the mental health. For such a reason, accurate measurements of stress level can be helpful to provide mechanisms for prevention and treatment. This paper proposes a procedure for the classification of different mental stress levels by using physiological signals provided by low invasive wearable devices. 17 healthy volunteers participated in this study. Three different mental states were elicited in them: a resting condition, a stressful cognitive state, and a sustained attention task. The acquired physiological signals were: a one lead electrocardiogram (ECG)…
2020
Recommender systems are information software that retrieves relevant items for users from massive sources of data. The variational autoencoder (VAE) has proven to be a promising approach for recommendation systems, as it can explore high-level user-item relations and extract contingencies from the input effectively. However, the previous variants of VAE have so far seen limited application to domain-specific recommendations that require additional side information. Hence, The Ensemble Variational Autoencoder framework for recommendations (EnsVAE) is proposed. This architecture specifies a procedure to transform sub-recommenders’ predicted utility matrix into interest probabilities that allo…
A platform for the development and the validation of HW IP components starting from reference software specifications
2008
Abstract Signal processing algorithms become more and more efficient as a result of the developments of new standards. It is particularly true in the field video compression. However, at each improvement in efficiency and functionality, the complexity of the algorithms is also increasing. Textual specifications, that in the past were the original form of specifications, have been substituted by reference software which became the starting point of any design flow leading to implementation. Therefore, designing an embedded application has become equivalent to port a generic software on a, possibly heterogeneous, embedded platform. Such operation is getting more and more difficult because of …
State of the Art in Information Security Policy Development
2020
Despite the prevalence of research that exists under the label of “information security policies” (ISPs), there is no consensus on what an ISP means or how ISPs should be developed. This article reviews state-of-the-art ISP development by examining a diverse sample of literature on the subject. The definition and function of an ISP is studied first, revealing a rich tapestry of different notions behind the same term. When looking at the broad picture of the research on ISP development methods, we find different phases and levels of detail. Analyzing the different views on the content, context, and strategy alignment provides for further understanding on the complexity of the matter. As an o…
Assessing the Performance of Interactive Multiobjective Optimization Methods
2021
Interactive methods are useful decision-making tools for multiobjective optimization problems, because they allow a decision-maker to provide her/his preference information iteratively in a comfortable way at the same time as (s)he learns about all different aspects of the problem. A wide variety of interactive methods is nowadays available, and they differ from each other in both technical aspects and type of preference information employed. Therefore, assessing the performance of interactive methods can help users to choose the most appropriate one for a given problem. This is a challenging task, which has been tackled from different perspectives in the published literature. We present a …
HyperLabelMe : A Web Platform for Benchmarking Remote-Sensing Image Classifiers
2017
HyperLabelMe is a web platform that allows the automatic benchmarking of remote-sensing image classifiers. To demonstrate this platform's attributes, we collected and harmonized a large data set of labeled multispectral and hyperspectral images with different numbers of classes, dimensionality, noise sources, and levels. The registered user can download training data pairs (spectra and land cover/use labels) and submit the predictions for unseen testing spectra. The system then evaluates the accuracy and robustness of the classifier, and it reports different scores as well as a ranked list of the best methods and users. The system is modular, scalable, and ever-growing in data sets and clas…
Higher-Fidelity Frugal and Accurate Quantile Estimation Using a Novel Incremental <italic>Discretized</italic> Paradigm
2018
Traditional pattern classification works with the moments of the distributions of the features and involves the estimation of the means and variances. As opposed to this, more recently, research has indicated the power of using the quantiles of the distributions because they are more robust and applicable for non-parametric methods. The estimation of the quantiles is even more pertinent when one is mining data streams. However, the complexity of quantile estimation is much higher than the corresponding estimation of the mean and variance, and this increased complexity is more relevant as the size of the data increases. Clearly, in the context of infinite data streams, a computational and sp…
Exact results for accepting probabilities of quantum automata
2001
One of the properties of Kondacs-Watrous model of quantum finite automata (QFA) is that the probability of the correct answer for a QFA cannot be amplified arbitrarily. In this paper, we determine the maximum probabilities achieved by QFAs for several languages. In particular, we show that any language that is not recognized by an RFA (reversible finite automaton) can be recognized by a QFA with probability at most 0.7726...
Word assembly through minimal forbidden words
2006
AbstractWe give a linear-time algorithm to reconstruct a finite word w over a finite alphabet A of constant size starting from a finite set of factors of w verifying a suitable hypothesis. We use combinatorics techniques based on the minimal forbidden words, which have been introduced in previous papers. This improves a previous algorithm which worked under the assumption of stronger hypothesis.