12 documents found, page 1 of 2
A super resolution method based on generative adversarial networks with quantum...
El amraoui, Khalid; Pu, Ziqiang; Koutti, Lahcen; Masmoudi, Lhoussaine; Valente de Oliveira, JOSÉSuper-resolution aims to enhance the quality of a low-resolution image to create a high-resolution one. Remarkable advances are witnessed in this field using machine learning techniques. This paper presents a superresolution method based on generative adversarial networks (GAN) with quantum feature enhancement. The proposed framework uses a feature enhancement layer inspired by the quantum superposition princip...
Sliced Wasserstein cycle consistency generative adversarial networks for fault ...
Pu, Ziqiang; Cabrera, Diego; Li, Chuan; Valente de Oliveira, JOSÉWe investigate the role of the loss function in cycle consistency generative adversarial networks (CycleGANs). Namely, the sliced Wasserstein distance is proposed for this type of generative model. Both the unconditional and the conditional CycleGANs with and without squeeze-and-excitation mechanisms are considered. Two data sets are used in the evaluation of the models, i.e., the well-known MNIST and a real-wo...
VGAN: generalizing MSE GAN and WGAN-GP for robot fault diagnosis
Pu, Ziqiang; Cabrera, Diego; Li, Chuan; Valente de Oliveira, JOSÉGenerative adversarial networks (GANs) have shown their potential for data generation. However, this type of generative model often suffers from oscillating training processes and mode collapse, among other issues. To mitigate these, this work proposes a generalization of both mean square error (mse) GAN and Wasserstein GAN (WGAN) with gradient penalty, referred to as VGAN. Within the framework of conditional W...
Feature discovery in NIR spectroscopy based Rocha pear classification
Daniel, Mariana; Guerra, Rui Manuel Farinha das Neves; Brazio, António; Rodrigues, Daniela; M. Cavaco, A.; Antunes, Maria DulceNon-invasive techniques for automatic fruit classification are gaining importance in the global agro-industry as they allow for optimizing harvesting, storage, management, and distribution decisions. Visible, near infra-red (NIR) diffuse reflectance spectroscopy is one of the most employed techniques in such fruit classification. Typically, after the acquisition of a fruit reflectance spectrum the wavelength do...
A comparison of dimension reduction techniques for support vector machine model...
Bai, Yun; Sun, Zhenzhong; Zeng, Bo; Long, Jianyu; Li, Lin; Valente de Oliveira, JOSÉ; Li, ChuanManufacturing quality prediction model, as an effective measure to monitor the quality in advance, has been developed using various data-driven techniques. However, multi-parameter in multi-stage of the modern manufacturing industry brings about the curse of dimensionality, leading to the difficulties for feature extraction, learning and quality modeling. To address this issue, three dimension reduction techniq...
Applying the coral reefs optimization algorithm for solving unequal area facili...
Garcia-Hernandez, L.; Salas-Morera, L.; Garcia-Hernandez, J. A.; Salcedo-Sanz, S.; Valente de Oliveira, JOSÉCoral Reefs Optimization (CRO) is a recently proposed evolutionary-type algorithm which has shown promising results to tackle many complex optimization problems. This paper discusses the performance of this meta-heuristic in Unequal Area Facility Layout Problems (UA-FLPs). The UA-FLP is an important problem in industrial production, which considers a rectangular region and a set of rectangular facilities. These...
Advances in intelligent computing for diagnostics, prognostics, and system heal...
Li, Chuan; Valente de Oliveira, JOSÉThis special issue of the Journal of Intelligent & 10 Fuzzy Systems on intelligent computing for diag11 nostics, prognostics, and system health management 12 is edited from a selection of papers which were 13 originally presented at SDPC 2017 – the 2017 Inter14 national Conference on Sensing, Diagnosis, and 15 Control, held in Shanghai, China, in August 2017. 16 The guest editors have accepted 41 papers with th...
Synthesis of probabilistic fuzzy classifiers using GK clustering and bayesian e...
Ledo, L.; Delgado, M. R.; Valente de Oliveira, JOSÉThe paper presents an automatic rule-base design of probabilistic fuzzy systems developed for classification tasks. The objective here is to present a methodology that allows the user to obtain a fuzzy classifier directly from training data, in which rules' antecedents are defined on the basis of clustering techniques and probabilistic consequents allow the presence of all classes in the same individual rule, e...
On asynchronous parallelization of order-based GA over grid-enabled heterogenou...
Valente de Oliveira, JOSÉ; Baltazar, Sérgio; Daniel, HelderIn real-world applications, the runtime of genetic algorithms (GAs) can be computationally demanding, an issue that can be mitigated using parallelization. The study evaluates the parallelization of order-based GAs using the island model in an asynchronous heterogeneous computing environment. The island model allows for a considerable number of migration topologies. The study offers a systematic review of the s...
Automatic feature extraction of time-series applied to fault severity assessmen...
Cabrera, Diego; Sancho, Fernando; Li, Chuan; Cerrada, Mariela; Sanchez, Rene-Vinicio; Pacheco, Fannia; Valente de Oliveira, JOSÉSignals captured in rotating machines to obtain the status of their components can be considered as a source of massive information. In current methods based on artificial intelligence to fault severity assessment, features are first generated by advanced signal processing techniques. Then feature selection takes place, often requiring human expertise. This approach, besides time-consuming, is highly dependent ...