Results 11 to 20 of about 742,455 (317)
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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Generalized SMASH imaging [PDF]
Magnetic Resonance in Medicine, 2001 AbstractA generalized parallel imaging method has been developed that uses coil profiles to generate missing k‐space lines. The proposed method is an extension of SMASH, which uses linear combinations of coil sensitivity profiles to synthesize spatial harmonics. In the generalized SMASH approach described here, coil sensitivity profiles are represented
Mark, Bydder +2 more
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Generic Isolated Cell Image Generator [PDF]
Cytometry Part A, 2019 AbstractBuilding automated cancer screening systems based on image analysis is currently a hot topic in computer vision and medical imaging community. One of the biggest challenges of such systems, especially those using state‐of‐the‐art deep learning techniques, is that they usually require a large amount of training data to be accurate.
Scalbert, Marin +2 more
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Generative Imaging and Image Processing via Generative Encoder
CoRR, 2019 This paper introduces a novel generative encoder (GE) model for generative imaging and image processing with applications in compressed sensing and imaging, image compression, denoising, inpainting, deblurring, and super-resolution. The GE model consists of a pre-training phase and a solving phase.
Lin Chen, Haizhao Yang
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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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Generalized Deep Image to Image Regression [PDF]
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 We present a Deep Convolutional Neural Network architecture which serves as a generic image-to-image regressor that can be trained end-to-end without any further machinery. Our proposed architecture: the Recursively Branched Deconvolutional Network (RBDN) develops a cheap multi-context image representation very early on using an efficient recursive ...
Venkataraman Santhanam +2 more
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Sketch-Guided Two-Stage Text-to-Image Generation with Spatial Control [PDF]
, 2023 Recent text-to-image diffusion models can produce high-quality images based only on textual prompts. However, it is difficult to correctly interpret instructions specifying the layout of a compositional space using only text.
Zhang, Tianyu, Xie, Haoran
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Optical and SAR Image Registration Based on Pseudo-SAR Image Generation Strategy
, 2023 The registration of optical and SAR images has always been a challenging task due to the different imaging mechanisms of the corresponding sensors. To mitigate this difference, this paper proposes a registration algorithm based on a pseudo-SAR image ...
Xinwei Li +4 more
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Generalized PCM Coding of Images [PDF]
IEEE Transactions on Image Processing, 2012 Pulse-code modulation (PCM) with embedded quantization allows the rate of the PCM bitstream to be reduced by simply removing a fixed number of least significant bits from each codeword. Although this source coding technique is extremely simple, it has a poor coding efficiency. In this paper, we present a generalized PCM (GPCM) algorithm for images that
José Prades Nebot +2 more
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The Challenges of Image Generation Models in Generating Multi-Component Images
CoRR, 2023 10 pages, 6 figures, and 3 ...
Tham Yik Foong +3 more
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