Results 41 to 50 of about 2,911,065 (235)
Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential
Patterns, 2020 Summary: Image analysis in the field of digital pathology has recently gained increased popularity. The use of high-quality whole-slide scanners enables the fast acquisition of large amounts of image data, showing extensive context and microscopic detail
Maximilian E. Tschuchnig +2 more
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Generative Adversarial Network (GAN) based Image-Deblurring
CoRR, 2022 90 pages, 35 figures, MS Thesis at the University of ...
Yuhong Lu, Nicholas Polydorides
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Understanding Generative Adversarial Networks [PDF]
, 2023 Generative adversarial networks (GANs) are a new technology impacting social, policy, and security discourses. The rise of GANs enables the creation of artificially generated hyper-realistic human faces.
Ludwig, Peyton
core
IEEE AccessGenerative Adversarial Networks (GANs) have emerged as a powerful type of generative model, particularly effective at creating images from textual descriptions.
Patibandla Chanakya +2 more
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ADAPTIVE MULTIMEDIA OPTIMIZATION USING GENERATIVE ADVERSARIAL NETWORKS AND ATTENTION-BASED DEEP FEATURE LEARNING FRAMEWORK [PDF]
ICTACT Journal on Image and Video ProcessingMultimedia systems have faced persistent challenges in maintaining perceptual quality under dynamic network and computational constraints. Traditional optimization techniques have struggled to preserve visual fidelity while adapting to heterogeneous ...
M. Subi Stalin, R. Prabakaran
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Generative Adversarial Networks in Brain Imaging: A Narrative Review
Journal of Imaging, 2022 Artificial intelligence (AI) is expected to have a major effect on radiology as it demonstrated remarkable progress in many clinical tasks, mostly regarding the detection, segmentation, classification, monitoring, and prediction of diseases.
Maria Elena Laino +5 more
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Advanced Materials Technologies, EarlyView.The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz +5 more
wiley +1 more source
Various Generative Adversarial Networks Model for Synthetic Prohibitory Sign Image Generation
Applied Sciences, 2021 A synthetic image is a critical issue for computer vision. Traffic sign images synthesized from standard models are commonly used to build computer recognition algorithms for acquiring more knowledge on various and low-cost research issues. Convolutional
Christine Dewi +3 more
doaj +1 more source
Using Novelty Seeking Reward Evolution Strategies to Train Generative Adversarial Networks [PDF]
, 2018 Generative Adversarial Networks (GANs) are a subclass of deep generative models that aim to implicitly learn to model a data distribution. While GANs have gained wide research attention, and achieved much success, when trained with first-order stochastic
Jabr, Khaled
core
On‐Chip Photonic Neural Network Architectures
Advanced Optical Materials, EarlyView.This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source