Search Results - "supervised autoencoder"

Bagging Supervised Autoencoder Classifier for credit scoring by Abdoli, Mahsan, Akbari, Mohammad, Shahrabi, Jamal

“… To mitigate these challenges, in this paper, we propose the Bagging Supervised Autoencoder Classifier (BSAC…”
Get full text

Predicting non-linear stress–strain response of mesostructured cellular materials using supervised autoencoder by Nakarmi, Sushan, Leiding, Jeffery A., Lee, Kwan-Soo, Daphalapurkar, Nitin P.

“…Recent breakthroughs in advanced manufacturing capabilities have made it possible to design and print sophisticated topologies of cellular structures using…”
Get full text

Improved semi-supervised autoencoder for deception detection by Fu, Hongliang, Lei, Peizhi, Tao, Huawei, Zhao, Li, Yang, Jing

“… This model updates and optimizes the semi-supervised autoencoder and it consists of two layers of encoder and decoder, and a classifier…”
Get full text

A semi-supervised autoencoder for autism disease diagnosis by Yin, Wutao, Li, Longhai, Wu, Fang-Xiang

“… In this paper, we proposed a semi-supervised autoencoder (AE) for autism diagnosis using functional connectivity (FC…”
Get full text

Novel Stacked Input-Enhanced Supervised Autoencoder Integrated With Gated Recurrent Unit for Soft Sensing by Tian, Ye, Xu, Yuan, Zhu, Qun-Xiong, He, Yan-Lin

“… In this article, a novel stacked input-enhanced supervised autoencoder (SISAE) integrated with gated recurrent unit (GRU) is proposed…”
Get full text

Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum by Jang, Hee-Deok, Kwon, Seokjoon, Nam, Hyunwoo, Chang, Dong Eui

“… In this paper, we propose a deep neural network utilizing a semi-supervised autoencoder (SSAE) for the classification of chemical gases based on FTIR spectra…”
Get full text

A Semi-Supervised Autoencoder-Based Approach for Protein Function Prediction by Dhanuka, Richa, Tripathi, Anushree, Singh, Jyoti P.

“…After the development of next-generation sequencing techniques, protein sequences are abundantly available. Determining the functional characteristics of these…”
Get full text

A personalized classification model using similarity learning via supervised autoencoder by Jo, Hyunjae, Jun, Chi-Hyuck

“… through a supervised autoencoder and calculates the similarity measure between observations in the transformed latent space…”
Get full text

Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder by Liang, Hanwen, Zhang, Qiong, Dai, Peng, Lu, Juwei

“… Specifically, we teach the model to capture broader variations of the feature distributions with a novel noise-enhanced supervised autoencoder (NSAE…”
Get full text

Forward and inverse design of kirigami via supervised autoencoder by Hanakata, Paul Z., Cubuk, Ekin D., Campbell, David K., Park, Harold S.

“… Here, we use a supervised autoencoder (SAE) to perform the inverse design of graphene kirigami, where predicting the ultimate stress or strain under tensile loading…”
Get full text

scSSA: A clustering method for single cell RNA-seq data based on semi-supervised autoencoder by Zhao, Jian-Ping, Hou, Tong-Shuai, Su, Yansen, Zheng, Chun-Hou

“…•In this study, We proposed to use semi-supervised autoencoder to reduce the dimension of data, because it makes good use of some existing label information…”
Get full text

Fishing Gear Pattern Recognition by Including Supervised Autoencoder Dimensional Reduction by Carlos, Hugo, Aranda, Ramon, Velasco, Mariana Rivera-De, Rodriguez-Gonzalez, Ansel Y., Mendez-Lopez, Maria Elena

“… Thus, our main contribution is how we propose data processing by including a supervised autoencoder dimensional reduction (SA-DR…”
Get full text

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images by Cheng, Jianhong, Zhao, Wei, Liu, Jin, Xie, Xingzhi, Wu, Shangjie, Liu, Liangliang, Yue, Hailin, Li, Junjian, Wang, Jianxin, Liu, Jun

“… In this study, we proposed a deep supervised autoencoder (DSAE) framework to automatically identify COVID-19 using multi-view features extracted from CT images…”
Get full text

Supervised autoencoder denoiser for non-stationarity in multi-session EEG-based BCI by Ofer, Avin, Ophir, Almagor, Yoav, Noah, Roman, Rosipal, Oren, Shriki

“…). In this study, we propose a novel method for cross-session BCI tasks that employs a supervised autoencoder to reduce session-specific information while preserving task-related signals…”
Get full text

Geometric feature knowledge-driven surrogate-based optimization via aerodynamic supervised autoencoder by Ma, Long, Wu, Xiaojing, Zuo, Zijun, Zhang, Weiwei

“…•An aerodynamic supervised autoencoder is proposed to learn geometric feature correlated with aerodynamic responses with limited aerodynamic data…”
Get full text

Captured multi-label relations via joint deep supervised autoencoder by Lian, Si-ming, Liu, Jian-wei, Lu, Run-kun, Luo, Xiong-lin

“… Meanwhile, it is not advisable to suppose that multiple labels are independent of each other. Therefore, we propose the deep supervised autoencoder as a generative model…”
Get full text

Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace by Zhou, Ping, Zhao, Peng, Ou, Zihui, Chai, Tianyou

“…This paper proposes a novel stacked semi-supervised autoencoder-regularized random vector functional-link networks (RVFLNs…”
Get full text

A semi-supervised autoencoder framework for joint generation and classification of breathing by Pastor-Serrano, Oscar, Lathouwers, Danny, Perkó, Zoltán

“…•Models of breathing motion using 1D convolutional neural networks and probabilistic autoencoders.•A novel semi-supervised algorithm based on Adversarial…”
Get full text

Supervised autoencoder MLP for financial time series forecasting by Bieganowski, Bartosz, Ślepaczuk, Robert

“…This paper investigates the enhancement of financial time series forecasting with the use of neural networks through supervised autoencoders, aiming to improve investment strategy performance…”
Get full text

Just-in-time updating soft sensor model of endpoint carbon content and temperature in BOF steelmaking based on deep residual supervised autoencoder by Yang, Lu, Liu, Hui, Chen, Fugang

“… Thus, this paper proposes a feature extraction model based on deep residual supervised autoencoder (DRSupAE…”
Get full text