Results 151 to 160 of about 113,519 (298)

Research on Damage Identification for Steel Frames Based on Convolutional Autoencoder and Correlation Function [PDF]

Y.B. Yang, Shuai Kang, Zifa Wang, Zongkai He, Teng Hui   +4 more
openalex   +1 more source

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder [PDF]

, 2020
Youngkyu Kim, Youngsoo Choi, David Widemann, Tarek I. Zohdi   +3 more
openalex   +1 more source

Language‐Guided Robot Grasping Based on Basic Geometric Shape Fitting

Advanced Intelligent Systems, EarlyView.
This article presents a language‐guided, model‐free grasping framework that integrates multimodal perception with primitive‐based geometric fitting. By explicitly modeling object geometry from RGB‐D data, the method enables semantically controllable grasp pose generation and achieves robust performance in both structured and cluttered real‐world ...
Qun Niu, Chuanlin Zhang, Tianyu Zhang, Jieliang Zhao, Tie Fu, Xuemei Chen   +5 more
wiley   +1 more source

Detecting Social Media Bots with Variational AutoEncoder and k-Nearest Neighbor [PDF]

, 2021
Xiujuan Wang, Qianqian Zhang, Kangfeng Zheng, Yi Sui, Siwei Cao, Yutong Shi   +5 more
openalex   +1 more source

Appraisal of Gene Expression‐Based Classifiers for Neuropsychiatric Disorders: A Meta‐Regression

American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.
ABSTRACT A substantial body of research examines the potential of gene‐expression‐based biomarkers for diagnosing and selecting treatments for neuropsychiatric disorders, yet no clear consensus has been reached regarding the influence of controllable factors such as study design and model selection on the performance of gene‐expression‐based ...
Ali Razavi, Brittany Arensman, Eric J. Barnett, Leo A. Lee, Stephen V. Faraone, Stephen J. Glatt, Jonathan L. Hess   +6 more
wiley   +1 more source

Hierarchical Complementary Enhanced Autoencoder Integrating Spatio‐Temporal Interaction Feature for Soft Sensor

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT To address the issues of neglecting the spatiotemporal correlations among process variables, low‐level features are vulnerable to noise interference, and the gradual loss of key information layer by layer during deep network training in traditional stacked autoencoder‐based soft‐sensor models, this paper proposes a hierarchical complementary ...
Xiaoping Guo, Jinghong Guo, Yuan Li
wiley   +1 more source

Ranking-Based Autoencoder for Extreme Multi-label Classification

, 2019
Wang Bingyu, Li Chen, Wei Sun, Kechen Qin, Kefeng Li, Hui Zhou   +5 more
openalex   +1 more source

Anomaly Detection With Conditional Variational Autoencoders

, 2020
Adrian Alan Pol, Victor Berger, G. Cerminara, Cécile Germain, Pierini, Maurizio   +4 more
openalex   +1 more source

A Novel Deep Temporal Feature Enhanced Just‐in‐Time Learning Framework for Predicting Rare Earth Component Content

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Real‐time online detection of rare earth element component contents is a crucial link in ensuring the stable production of the rare earth extraction and separation industry and improving the quality of rare earth products. The traditional methods for predicting the content of rare earth element components based on just‐in‐time learning fail to
Zhaohui Huang, Liangfang Liao, Chunfa Liao, Hui Zhang, Tao Qi, Rongxiu Lu, Wenhao Dai   +6 more
wiley   +1 more source

Gaussian AutoEncoder

, 2018
Generative AutoEncoders require a chosen probability distribution in latent space, usually multivariate Gaussian. The original Variational AutoEncoder (VAE) uses randomness in encoder - causing problematic distortion, and overlaps in latent space for distinct inputs.
openaire   +2 more sources