Results 41 to 50 of about 60,338 (274)

Development of a Machine-Learning Intrusion Detection System and Testing of Its Performance Using a Generative Adversarial Network

Sensors, 2023
Intrusion detection and prevention are two of the most important issues to solve in network security infrastructure. Intrusion detection systems (IDSs) protect networks by using patterns to detect malicious traffic. As attackers have tried to dissimulate
Andrei-Grigore Mari, Daniel Zinca, Virgil Dobrota   +2 more
doaj   +1 more source

Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models

, 2018
Adversarial learning of probabilistic models has recently emerged as a promising alternative to maximum likelihood. Implicit models such as generative adversarial networks (GAN) often generate better samples compared to explicit models trained by maximum
Dhar, Manik, Ermon, Stefano, Grover, Aditya   +2 more
core   +1 more source

2D Nanomaterials Toward Function‐Ready Superlubricity in Advanced Microsystems

Advanced Materials, EarlyView.
A unified framework links structural and transformation superlubricity with microsystem functions and deployment requirements. Mechanisms, device architectures, integration strategies, AI‐guided discovery, and benchmarking protocols are connected to define function‐ready superlubricity in advanced microsystems.
Yushan Geng, Jun Yang, Yong Yang
wiley   +1 more source

Investigating the effect of loss functions on single-image GAN performance

Journal of Innovative Science and Engineering
Loss functions are crucial in training generative adversarial networks (GANs) and shaping the resulting outputs. These functions, specifically designed for GANs, optimize generator and discriminator networks together but in opposite directions.
Eyyup YİLDİZ, Mehmet Erkan YUKSEL, Selcuk SEVGEN   +2 more
doaj   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

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, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Adversarial Examples Detection for XSS Attacks Based on Generative Adversarial Networks

IEEE Access, 2020
Models based on deep learning are prone to misjudging the results when faced with adversarial examples. In this paper, we propose an MCTS-T algorithm for generating adversarial examples of cross-site scripting (XSS) attacks based on Monte Carlo tree ...
Xueqin Zhang, Yue Zhou, Songwen Pei, Jingjing Zhuge, Jiahao Chen   +4 more
doaj   +1 more source

iVAE-GAN: Identifiable VAE-GAN Models for Latent Representation Learning

IEEE Access, 2022
Remarkable progress has been made within nonlinear Independent Component Analysis (ICA) and identifiable deep latent variable models. Formally, the latest nonlinear ICA theory enables us to recover the true latent variables up to a linear transformation ...
Bjorn Uttrup Dideriksen, Kristoffer Derosche, Zheng-Hua Tan   +2 more
doaj   +1 more source

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

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

Recent Advances of Generative Adversarial Networks in Computer Vision

IEEE Access, 2019
The appearance of generative adversarial networks (GAN) provides a new approach and framework for computer vision. Compared with traditional machine learning algorithms, GAN works via adversarial training concept and is more powerful in both feature ...
Yang-Jie Cao, Li-Li Jia, Yong-Xia Chen, Nan Lin, Cong Yang, Bo Zhang, Zhi Liu, Xue-Xiang Li, Hong-Hua Dai   +8 more
doaj   +1 more source