[PDF] Top 20 Generative Adversarial Networks for Realistic Synthesis of Hyperspectral Samples
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Generative Adversarial Networks for Realistic Synthesis of Hyperspectral Samples
... on Generative Adversarial Networks to generate an arbitrary large number of hyperspectral samples matching the distribution of any dataset, annotated or ...properties ... Voir le document complet
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Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views
... distribution of the data and create new samples ...generating realistic images with low variability [7, 15, ...distribution of the data or if it is generated by ...usefulness of the ... Voir le document complet
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On the Use of Generative Adversarial Networks for Aircraft Trajectory Generation and Atypical Approach Detection
... use of data generative models to learn real approach flight path probability distributions and identify flights that do not follow these ...use of Generative Adversarial Networks ... Voir le document complet
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Semantic Segmentation using Adversarial Networks
... number of architectural design choices that enable stable training of generative models that are able to synthesize realistic ...“deconvolutional” networks g(·) that progressively ... Voir le document complet
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Realistic synthesis of brain tumor resection ultrasound images with a generative adversarial network
... with generative adversarial network,” in [SPIE Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling ], 11315, 54–60 ...registration of three-dimensional ultrasound and ... Voir le document complet
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Interactive Example-Based Terrain Authoring with Conditional Generative Adversarial Networks
... need for authoring tools able to create realistic terrains with simple user-inputs and with high user ...set of terrain synthesizers dedicated to speci�c ...Conditional Generative ... Voir le document complet
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Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets
... Generative Adversarial Networks – Recently, GANs have shown to be extremely efficient for synthesizing realis- tic ...used for several applications in- cluding image synthesis ... Voir le document complet
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Comparing Representations for Audio Synthesis Using Generative Adversarial Networks
... Dataset For this work, we make use of the NSynth dataset [26], consisting of approximately 300,000 single-note audios played by more than 1,000 different instruments from 10 different ...The ... Voir le document complet
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Adaptive Density Estimation for Generative Models
... makes adversarial training of such models prohibitively ...high-quality samples typical of adversarial models, (ii) provides a likelihood measure on the entire image space, and (iii) ... Voir le document complet
25
Realistic Plant Modeling from Images based on Analysis-by-Synthesis
... [15] model different species of trees using images of tree samples from the real world which are analysed to extract similar elements.. A stochastic model to assemble these elements is a[r] ... Voir le document complet
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Capturing data and realistic 3D models for cued speech analysis and audiovisual synthesis
... understanding of the kinematics of the different segments involved in the production of MCS might lower the number of necessary ...evaluations of the reconstructed gestures and the ... Voir le document complet
7
Generative models for natural images
... objective for generative ...task. For example, if the purpose is to generate samples from a (conditional) distribution to perform image super-resolution (where the goal is to enhance the ... Voir le document complet
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Realistic Plant Modeling from Images Based on Analysis-by-Synthesis
... model of a plant without any human interaction from images with possibly no visible ...knowledge of the plant species, we propose a simple fully-automatic process to extract the structure of a plant ... Voir le document complet
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Adversarial Games for Particle Physics
... • The generation process is often not uniquely specified or known exactly, hence systematic uncertainties.. • Parametrization through.[r] ... Voir le document complet
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Detection error exponent for spatially dependent samples in random networks
... analysis for the test of simple hy- potheses with general distributions exists [2], [4], but closed- form expressions are possible only for certain ...analysis for homogeneous Gauss-Markov ... Voir le document complet
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Adversarial Games for Particle Physics
... • Adversarial training = indirectly specifying complicated loss functions. For generation[r] ... Voir le document complet
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Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI
... 3. EXPERIMENTS AND RESULTS 3.1. Datasets and network training To assess the ability to reconstruct HR volume and segment the cerebral cortex , we applied the proposed method on T2- weighted (T2w) MR images of the ... Voir le document complet
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LIGHT FIELD IMAGE CODING USING DUAL DISCRIMINATOR GENERATIVE ADVERSARIAL NETWORK AND VVC TEMPORAL SCALABILITY
... Index Terms— Light Field, Deep Learning, D2GAN, VVC, Coding Structure, RDO. 1. INTRODUCTION Light Field (LF) image can be captured and sampled by a plenoptic camera composed of an array of microlens such as ... Voir le document complet
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Structured prediction and generative modeling using neural networks
... neural networks to effectively model data with sequen- tial ...forms of data for which both the order and the structure of the information is ncredibly ...example of this type of ... Voir le document complet
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Reconstructing faces from fMRI patterns using deep generative neural networks
... realm of face processing, can bring us closer and closer to an adequate model of latent human brain ...potential for future explorations of face processing and representation in the human ... Voir le document complet
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