Results 41 to 50 of about 128,746 (262)
Advanced Science, EarlyView.We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu +7 more
wiley +1 more source
Adaptive Density Estimation for Generative Models [PDF]
, 2019 Unsupervised learning of generative models has seen tremendous progress over recent years, in particular due to generative adversarial networks (GANs), variational autoencoders, and flow-based models.
Alahari, Karteek +4 more
core +2 more sources
A Dual Attentive Generative Adversarial Network for Remote Sensing Image Change Detection [PDF]
, 2023 Luyi Qiu +3 more
openalex +1 more source
DOOM Level Generation Using Generative Adversarial Networks [PDF]
2018 IEEE Games, Entertainment, Media Conference (GEM), 2018 We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analysed the levels and extracted several topological features. Then, for each level, we extracted a set of images identifying the occupied area, the height map, the walls, and the position of game objects.
GIACOMELLO, EDOARDO +2 more
openaire +3 more sources
Advanced Science, EarlyView.A neuromorphic computing platform using spin‐orbit torque‐controlled magnetic textures is reported. The device implements bio‐inspired synaptic functions and achieves high performance in both pattern recognition (>93%) and combinatorial optimization (>95%), enabling unified processing of cognitive and optimization tasks.
Yifan Zhang +13 more
wiley +1 more source
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 +3 more
openaire +2 more sources
Advanced Science, EarlyView.scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley +1 more source
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
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 +13 more
wiley +1 more source
Adversarial Example Detection and Classification With Asymmetrical Adversarial Training
, 2020 The vulnerabilities of deep neural networks against adversarial examples have become a significant concern for deploying these models in sensitive domains.
Kolouri, Soheil +2 more
core