Results 81 to 90 of about 134,465 (305)

Flow-based network traffic generation using Generative Adversarial Networks [PDF]

Computers & Security, 2019
Flow-based data sets are necessary for evaluating network-based intrusion detection systems (NIDS). In this work, we propose a novel methodology for generating realistic flow-based network traffic. Our approach is based on Generative Adversarial Networks (GANs) which achieve good results for image generation.
Ring, Markus, Schlör, Daniel, Landes, Dieter, Hotho, Andreas   +3 more
openaire   +2 more sources

His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models

Advanced Science, EarlyView.
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li, Tianqi Su, Bin Zhang, Wenkai Han, Sibin Zhang, Guiyin Sun, Yuwei Cong, Xin Chen, Jiping Qi, Yujie Wang, Shiguang Zhao, Hongxue Meng, Peng Liang, Xin Gao   +13 more
wiley   +1 more source

VAE-WACGAN: An Improved Data Augmentation Method Based on VAEGAN for Intrusion Detection

Sensors
To address the class imbalance issue in network intrusion detection, which degrades performance of intrusion detection models, this paper proposes a novel generative model called VAE-WACGAN to generate minority class samples and balance the dataset. This
Wuxin Tian, Yanping Shen, Na Guo, Jing Yuan, Yanqing Yang   +4 more
doaj   +1 more source

Automatic Design System with Generative Adversarial Network and Convolutional Neural Network for Optimization Design of Interior Permanent Magnet Synchronous Motor [PDF]

, 2021
Yuki Shimizu, Shigeo Morimoto, Masayuki Sanada, Yukinori Inoue   +3 more
openalex   +1 more source

A Bottom‐Up Design Framework for Multifunctional Lattice Metamaterials

Advanced Science, EarlyView.
This study introduces a generative AI framework for designing multifunctional lattice metamaterials. The method combines 3D Gaussian voxel generation with deep learning, enabling greater design freedom and structural performance. The optimized lattice metamaterials achieve enhanced energy absorption by 40–200% compared to conventional structures and ...
Zongxin Hu, Quanqing Tao, Junhao Ding, Shuo Qu, Haitao Ye, Jun Wei Chua, Tianxiao Niu, Rui Li, Winston Wai Shing Ma, Haoming Mo, Hui Liu, Wei Zhai, Xinwei Li, Xu Song   +13 more
wiley   +1 more source

An End-to-End Conditional Random Fields and Skip-Connected Generative Adversarial Segmentation Network for Remote Sensing Images

Remote Sensing, 2019
Semantic segmentation is an important process of scene recognition with deep learning frameworks achieving state of the art results, thus gaining much attention from the remote sensing community.
Chu He, Peizhang Fang, Zhi Zhang, Dehui Xiong, Mingsheng Liao   +4 more
doaj   +1 more source

Phase space sampling and operator confidence with generative adversarial networks

, 2017
We demonstrate that a generative adversarial network can be trained to produce Ising model configurations in distinct regions of phase space. In training a generative adversarial network, the discriminator neural network becomes very good a discerning ...
Mills, Kyle, Tamblyn, Isaac
core  

Learnable Diffusion Framework for Mouse V1 Neural Decoding

Advanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng, Peter S. Schwendeman, Yuanfang Guan   +2 more
wiley   +1 more source

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

Advanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang, Bowen Fu, Chuanchao Zhang, Xiaoping Liu   +3 more
wiley   +1 more source

A generative adversarial network to Reinhard stain normalization for histopathology image analysis

Ain Shams Engineering Journal
Histopathology image analysis is paramount importance for accurate diagnosing diseases and gaining insight into tissue properties. The significant challenge of staining variability continues.
Afnan M. Alhassan
doaj   +1 more source