Results 11 to 20 of about 14,068,918 (254)
3D digital relief generation. [PDF]
This thesis investigates a framework for generating reliefs. Relief is a special kind of sculptured artwork consisting of shapes carved on a surface so as to stand out from the surrounding background.
Wang, Meili
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A study on diffusion probabilistic models for image generation [PDF]
, 2023 Diffusion probabilistic models have emerged as powerful tools for image generation and synthesis tasks. This research delves into the intricate relationship between the hyperparameters of these models and the underlying hardware, aiming to provide ...
Munoz, Roman
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A GENETIC APROACH FOR AUTOMATED IMAGE GENERATION: GRAYSCALE IMAGE GENERATION
Journal of Engineering, 2005 Non photorealistic rendering is a new research field in the areas of computer graphics. The goal is to give a more natural feel to computer generated images, by simulating various artistic techniques and to give the sense of an image without reproducing
Bara'a Ali Attea, Aminna Dahim Aboud
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Localization-Aware Adaptive Pairwise Margin Loss for Fine-Grained Image Recognition
IEEE Access, 2021 Fine-grained image recognition is a highly challenging problem due to subtle differences between images. There are many attempts to solve fine-grained image recognition problems using data augmentation, jointly optimizing deep metric learning.
Taehung Kim, Hoseong Kim, Hyeran Byun
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Study of image characteristics on digital image correlation error assessment [PDF]
, 2009 In this paper, errors related to digital image correlation (DIC) technique applied to measurements of displacements are estimated. This work is based on the generation of synthetic images representative of real speckle patterns.
Fazzini, Marina +7 more
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Generative convolution layer for image generation
Neural Networks, 2022 This paper introduces a novel convolution method, called generative convolution (GConv), which is simple yet effective for improving the generative adversarial network (GAN) performance. Unlike the standard convolution, GConv first selects useful kernels compatible with the given latent vector, and then linearly combines the selected kernels to make ...
Seung Park, Yong-Goo Shin
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Image analysis for 3D modeling, rendering, and virtual view generation
, 2022 S.231-53The generation of virtual environments for telepresence systems, interactive viewing, and immersion in remote 3D-scenarios is an expanding and very promising research field.
Kruse, S., Ebroul Izquierdo, M.
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HRGAN: A Generative Adversarial Network Producing Higher-Resolution Images than Training Sets
Sensors, 2022 The generative adversarial network (GAN) has demonstrated superb performance in generating synthetic images in recent studies. However, in the conventional framework of GAN, the maximum resolution of generated images is limited to the resolution of real ...
Minyoung Park, Minhyeok Lee, Sungwook Yu
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Image description generation model with the attention mechanism.
, 2023 Image description generation model with the attention mechanism.
Yi Wang (32470)
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Frontiers in MedicineDiffusion models, a class of deep learning models based on probabilistic generative processes, progressively transform data into noise and then reconstruct the original data through an inverse process.
Yan Liu +6 more
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