Results 81 to 90 of about 3,042,897 (294)
Solid Harmonic Wavelet Bispectrum for Image Analysis
Advanced Science, EarlyView.The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
An Introduction to Generative Adversarial Networks
, 2019 This thesis is a survey of the mathematical theory of Generative Adversarial Networks (GANs).
Paget, Bryan
core +1 more source
A Brief History of Generative Adversarial Networks
, 2022 Generative Adversarial Networks (GANs) are a class of Deep Neural Networks that have the ability to generate realistic synthetic data including but not limited to images, text, or even videos.
Sharma, Parth
core +1 more source
Generative Adversarial Networks Unlearning
IEEE Transactions on Dependable and Secure ComputingAs machine learning continues to develop, and data misuse scandals become more prevalent, individuals are becoming increasingly concerned about their personal information and are advocating for the right to remove their data. Machine unlearning has emerged as a solution to erase training data from trained machine learning models. Despite its success in
Hui Sun +3 more
openaire +4 more sources
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Generative adversarial networks enhanced location privacy in 5G networks
, 2020 Generative adversarial networks enhanced location privacy in 5G ...
J Zhang (7490018) +5 more
core
Generative Multi-Adversarial Networks
CoRR, 2016 Generative adversarial networks (GANs) are a framework for producing a generative model by way of a two-player minimax game. In this paper, we propose the \emph{Generative Multi-Adversarial Network} (GMAN), a framework that extends GANs to multiple discriminators.
Ishan P. Durugkar +2 more
openaire +4 more sources
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Optoelectronic generative adversarial networks
Communications PhysicsRecent breakthroughs in artificial intelligence generative content technology are driving transformational change. Diffractive optical networks offer a promising solution for high-speed, low-power generative models.
Jumin Qiu +5 more
doaj +1 more source
A Review of the Research and Development of Adversarial Generative Networks in Interior Graphic Design [PDF]
ITM Web of ConferencesThis study provides a comprehensive overview of the research and development of adversarial generative networks in interior graphic design. With the continuous development of adversarial generative networks, the level of Generative Adversarial Networks ...
Yang Haonan
doaj +1 more source