Suchergebnisse - conditioning variational (autoencoder(cave) OR autoencoder(cae))

Dall-e Brain : Generation of 2D T1-w, T2-w, and FLAIR MRI images using a prompt

Autoren: El-Allaly, Souhail Breuil, Julie Bibard-Grau, Emma et al.

Weitere Verfasser: El-Allaly, Souhail Breuil, Julie Bibard-Grau, Emma et al.

Quelle: 3e édition du Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM 2025).
https://hal.science/hal-05013997
3e édition du Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM 2025)., Mar 2025, Nice, France

Schlagwörter: Registration, Image Encoder/Decoder, Variational AutoEncoder, Latent Diffusion Model, Text prompt conditioning, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-IM]Computer Science [cs]/Medical Imaging

Geographisches Schlagwort: Nice, France

Time: Nice, France

Verfügbarkeit: https://hal.science/hal-05013997
https://hal.science/hal-05013997v1/document
https://hal.science/hal-05013997v1/file/Poster_Dalle_Brain_IABM_TG_SE_vfi_3.pdf

Anomaly Detection for Charging Piles Based on Conditional Variational Autoencoder.

Autoren: Wang, Chuanjun Lu, Yinyu Wang, Mingxin et al.

Quelle: International Transactions on Electrical Energy Systems; 9/23/2025, Vol. 2025, p1-12, 12p

Schlagwörter: ELECTRIC vehicles, SUPERVISED learning, PROBABILISTIC generative models, OUTLIER detection, SIGNAL detection, DISTRIBUTION (Probability theory), INFRASTRUCTURE (Economics)

Adaptive Neural Network System for Detecting Unauthorised Intrusions Based on Real-Time Traffic Analysis.

Autoren: Vladov, Serhii Vysotska, Victoria Lytvyn, Vasyl et al.

Quelle: Computation; Sep2025, Vol. 13 Issue 9, p221, 42p

Schlagwörter: INTRUSION detection systems (Computer security), ANOMALY detection (Computer security), KALMAN filtering, LATENT variables, INTERNET security, TRAFFIC monitoring, MACHINE learning, INTELLIGENT networks

Parallel Interaction Spatiotemporal Constrained Variational Autoencoder for Soft Sensor Modeling.

Autoren: Zhu, Xiuli Damarla, Seshu Kumar Hao, Kuangrong et al.

Quelle: IEEE Transactions on Industrial Informatics; Aug2022, Vol. 18 Issue 8, p5190-5198, 9p

Human Activity Recognition Using Convolutional Autoencoder and Advanced Preprocessing.

Autoren: Zaoui, Chaimae Benabbou, Faouzia Ettaoufik, Abdelaziz et al.

Quelle: International Journal of Online & Biomedical Engineering; 2024, Vol. 20 Issue 4, p144-159, 16p

Designing metamaterials with programmable nonlinear responses and geometric constraints in graph space.

Autoren: Maurizi, Marco Xu, Derek Wang, Yu-Tong et al.

Quelle: Nature Machine Intelligence; Jul2025, Vol. 7 Issue 7, p1023-1036, 14p

GANSim‐3D for Conditional Geomodeling: Theory and Field Application.

Autoren: Song, Suihong Mukerji, Tapan Hou, Jiagen et al.

Quelle: Water Resources Research; Jul2022, Vol. 58 Issue 7, p1-34, 34p

Schlagwörter: KARST, GENERATIVE adversarial networks, FACIES

Geografische Kategorien: CHINA

Convolutional Autoencoder Based Feature Extraction and Clustering for Customer Load Analysis.

Autoren: Ryu, Seunghyoung Choi, Hyungeun Lee, Hyoseop et al.

Quelle: IEEE Transactions on Power Systems; Mar2020, Vol. 35 Issue 2, p1048-1060, 13p

Schlagwörter: FEATURE extraction, DEEP learning, ARTIFICIAL neural networks, DATA compression, SMART meters, DATA transmission systems

Stochastic Modeling of Thin Mud Drapes Inside Point Bar Reservoirs With ALLUVSIM‐GANSim.

Autoren: Hu, Xun Song, Suihong Hou, Jiagen et al.

Quelle: Water Resources Research; Jun2024, Vol. 60 Issue 6, p1-24, 24p

Schlagwörter: MARKOV chain Monte Carlo, GENERATIVE adversarial networks, MUD, DRAPERIES, STOCHASTIC models, BRAIDED rivers

Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis.

Autoren: Flores, Mario Liu, Zhentao Zhang, Tinghe et al.

Quelle: Briefings in Bioinformatics; Jan2022, Vol. 23 Issue 1, p1-31, 31p

Schlagwörter: DEEP learning, GENERATIVE adversarial networks, MACHINE learning, ELECTRONIC data processing

Self‐supervised representation learning of metro interior noise based on variational autoencoder and deep embedding clustering.

Autoren: Wang, Yang Xiao, Hong Zhang, Zhihai et al.

Quelle: Computer-Aided Civil & Infrastructure Engineering; 2/4/2025, Vol. 40 Issue 4, p503-522, 20p

Schlagwörter: TRANSPORTATION noise, SIGNAL denoising, PATTERN perception, FAULT diagnosis, LATENT variables, MACHINE learning, EMPIRICAL research

An autoencoder driven deep learning geospatial approach to flood vulnerability analysis in the upper and middle basin of river Damodar.

Autoren: Thappitla, Rohit Srinivas Villuri, Vasanta Govind Kumar Kumar, Satish

Quelle: Scientific Reports; 9/30/2025, Vol. 15 Issue 1, p1-13, 13p

Schlagwörter: DEEP learning, AUTOENCODERS, K-means clustering, RAPIDS, CONVOLUTIONAL neural networks, FLOOD risk, RISK assessment, GEOSPATIAL data

European Heart Journal (2024) 45 (Suppl 1).

Quelle: European Heart Journal; 2024 Supplement, Vol. 45, p1-5865, 5865p

Schlagwörter: MEDICAL sciences, GLOBAL longitudinal strain, VENA cava inferior, LEFT heart ventricle, HEART septum, HEART failure, STRESS echocardiography, ACOUSTIC radiation force impulse imaging

Heartbeat detection and personal authentication using a 60 GHz Doppler sensor.

Autoren: Asano, Takuma Izumi, Shintaro Kawaguchi, Hiroshi

Quelle: Frontiers in Digital Health; 2025, p1-12, 12p

Schlagwörter: PATIENT monitoring equipment, BIOLOGICAL models, RESEARCH funding, SOUND spectrography, BIOMETRY, HEART beat, ELECTROCARDIOGRAPHY, SECURITY systems, TECHNOLOGY, PATIENT monitoring, MICROWAVES, WAVE analysis, ALGORITHMS

Variational autoencoders for 3D data processing.

Autoren: Molnár, Szilárd Tamás, Levente

Quelle: Artificial Intelligence Review; Feb2024, Vol. 57 Issue 2, p1-53, 53p

Continual learning approaches for anomaly detection.

Autoren: Pezze, Davide Dalle Anello, Eugenia Masiero, Chiara et al.

Quelle: Evolving Systems; Dec2025, Vol. 16 Issue 4, p1-20, 20p

A Review of Human Emotion Synthesis Based on Generative Technology.

Autoren: Ma, Fei Xie, Yifan Li, Yukan et al.

Quelle: IEEE Transactions on Affective Computing; Oct-Dec2025, Vol. 16 Issue 4, p2579-2598, 20p

Enhancing Automotive Paint Curing Process Efficiency: Integration of Computational Fluid Dynamics and Variational Auto-Encoder Techniques.

Autoren: Pendar, Mohammad-Reza Cândido, Silvio Páscoa, José Carlos et al.

Quelle: Sustainability (2071-1050); Apr2025, Vol. 17 Issue 7, p3091, 35p

Health Prognostics Classification with Autoencoders for Predictive Maintenance of HVAC Systems.

Autoren: Tian, Ruiqi Gomez-Rosero, Santiago Capretz, Miriam A. M.

Quelle: Energies (19961073); Oct2023, Vol. 16 Issue 20, p7094, 21p

Schlagwörter: AIR filters, HEATING, AIR ducts, HEATING & ventilation industry, ENVIRONMENTAL quality

A Deep Generative Model for the Simulation of Discrete Karst Networks.

Autoren: Lauzon, Dany Straubhaar, Julien Renard, Philippe

Quelle: Earth & Space Science; Oct2025, Vol. 12 Issue 10, p1-22, 22p

Schlagwörter: GRAPH neural networks, KARST, PROBABILISTIC generative models, COMPUTER simulation, TOPOLOGY, DEEP learning, HYDROGEOLOGY