Generative Adversarial Network (GAN)
Generating 3D Models Using 3D Generative Adversarial Network
... 3D Generative-Adversarial-Network(3D-GAN) which produces 3 Dimensional structure from a latent vector by using the modern advancement in convolution ...
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GANGs: Generative Adversarial Network Games
... Generative Adversarial Networks (GAN) have become one of the most successful frameworks for unsupervised generative ...introduce Generative Adversarial Network Games ...
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A Sensor Image Super-Resolution via Advanced Generative Adversarial Network
... Advanced Generative Adversarial Network ...for generative model to generate a plausible-looking ...previous GAN algorithms for super-resolution ...
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An Effective Feature Selection With Generative Adversarial Network (GAN) Model For Stock Market Prediction
... Abstract: At present days, the prediction of stock prices is very complicated as it depends on various factors. Several researches have been done to foresee the stock prices which will be helpful for users to identify ...
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Active Generative Adversarial Network for Image Classification
... a generative adversarial network (GAN) has been inte- grated with active learning to generate good candidates to be presented to the ...tional GAN to generate informative samples with a ...
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Pun GAN: Generative Adversarial Network for Pun Generation
... a generative adversarial network for pun ...Pun- GAN does not require any pun corpus, it can still enhance the ambiguity of sentence produced by the generator via the reward from the ...
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Improved Wasserstein conditional generative adversarial network speech enhancement
... the generative adversarial network has achieved excellent results with large quantities of data, but performance in the low-data regime and tasks like unseen data learning still lag ...Conditional ...
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Yet Another Text Captcha Solver:A Generative Adversarial Network Based Approach
... Despite several attacks have been proposed, text-based CAPTCHAs 1 are still being widely used as a security mechanism. One of the reasons for the pervasive use of text captchas is that many of the prior attacks are ...
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Diversity Promoting GAN: A Cross Entropy Based Generative Adversarial Network for Diversified Text Generation
... are given the same ranking. The inter-annotator agreement is satisfactory considering the difficulty in the human evaluation. The Pearson’s correla- tion coefficient is 0.76 on diversity, 0.59 on flu- ency and 0.27 on ...
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Open Event Extraction from Online Text using a Generative Adversarial Network
... various GAN based approaches have been explored for many applications, none of these approaches tackles open-domain event extraction from online ...novel GAN- based event extraction model called ...most ...
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Open event extraction from online text using a generative adversarial network
... various GAN based approaches have been explored for many applications, none of these approaches tackles open-domain event extraction from online ...novel GAN- based event extraction model called ...most ...
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Enhancing neural non-intrusive load monitoring with generative adversarial networks
... a Generative Adversarial Network to model appliance load profiles in NILM and the idea to complement the energy-based confusion ...the GAN-based disaggregation approaches, proposed the ...
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Self regulation: Employing a Generative Adversarial Network to Improve Event Detection
... Due to the ability of encoding and map- ping semantic information into a high- dimensional latent feature space, neural networks have been successfully used for detecting events to a certain extent. How- ever, such a ...
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Generative Adversarial Networks: A Comparative Analysis
... various generative adversarial networks ...Conditional Generative Adversarial Networks (CGAN), Star generative adversarial network (StarGAN) and Cycle generative ...
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Spatio-temporal silhouette sequence reconstruction for gait recognition against occlusion
... deep generative adversarial network ...proposed generative network, we use adversarial loss based on triplet hinge loss incorporating Wasserstein GAN ...first ...
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Network Simulated Generation of Human Faces with Expressions and Orientations for Deep Learning Classification
... Wasserstein generative adversarial network (WGAN) structure used by Martin et ...training GAN is complicated and ...neural network, implying that an equilibrium between the generator ...
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Vol 6, No 4 (2020)
... a generative adversarial network (GAN) model that is trained with human eye fixations to predict saliency, and the depth information provided by an RGB-D ...
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Dialectical GAN for SAR Image Translation: From Sentinel-1 to TerraSAR-X
... Keywords: dialectical generative adversarial network; image translation; Sentinel-1; TerraSAR-X.. Introduction 28.[r] ...
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Wasserstein Generative Adversarial Privacy Networks
... “generative adversarial privacy” wherein a variant of a generative adversarial network is used: rather than learning the probability distribution, their method directly tries to find an ...
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A Deep Learning Model of Perception in Color-Letter Synesthesia
... Keywords: synesthesia; deep learning network; color perception; generative adversarial network; 15.. cognitive modeling; character recognition; GPU computing 16.[r] ...
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