Results 61 to 70 of about 134,465 (305)

Missing Data Imputation Method Combining Random Forest and Generative Adversarial Imputation Network

Sensors
(1) Background: In order to solve the problem of missing time-series data due to the influence of the acquisition system or external factors, a missing time-series data interpolation method based on random forest and a generative adversarial ...
Hongsen Ou, Yunan Yao, Yi He
doaj   +1 more source

Avocodo: Generative Adversarial Network for Artifact-free Vocoder [PDF]

, 2022
Taejun Bak, Junmo Lee, Hanbin Bae, Jinhyeok Yang, Jae‐Sung Bae, Young-Sun Joo   +5 more
openalex   +1 more source

Generating Adversarial Examples with Adversarial Networks [PDF]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples resulting from adding small-magnitude perturbations to inputs. Such adversarial examples can mislead DNNs to produce adversary-selected results. Different attack strategies have been proposed to generate adversarial examples, but how to produce them with high ...
Xiao, Chaowei, Li, Bo, Zhu, Jun-Yan, He, Warren, Liu, Mingyan, Song, Dawn   +5 more
openaire   +2 more sources

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

Optoelectronic generative adversarial networks

Communications Physics
Recent 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, Ganqing Lu, Tingting Liu, Dejian Zhang, Shuyuan Xiao, Tianbao Yu   +5 more
doaj   +1 more source

HGAN: Hyperbolic Generative Adversarial Network

IEEE Access, 2021
Recently, Hyperbolic Spaces in the context of Non-Euclidean Deep Learning have gained popularity because of their ability to represent hierarchical data.
Diego Lazcano, Nicolas Fredes Franco, Werner Creixell   +2 more
doaj   +1 more source

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

Advanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao, Yinzhao Dong, Ji Ma, Peng Lu   +3 more
wiley   +1 more source

Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution Strategies [PDF]

, 2022
Víctor Costa, Nuno Lourenço, João Correia, Penousal Machado   +3 more
openalex   +1 more source

Generative Adversarial Networks: Recent Developments [PDF]

, 2019
10 ...
Zamorski, Maciej, Zdobylak, Adrian, Zięba, Maciej, Świątek, Jerzy   +3 more
openaire   +2 more sources

Multi-agent Diverse Generative Adversarial Networks [PDF]

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018
This is an updated version of our CVPR'18 paper with the same title.
Arnab Ghosh, Viveka Kulharia, Vinay Namboodiri, Philip H.S. Torr, Puneet K. Dokania   +4 more
openaire   +2 more sources