Suchergebnisse - "autoencoder model"

Knowledge-integrated autoencoder model von Lazebnik, Teddy, Simon-keren, Liron

“… Data encoding is a common and central operation in most data analysis tasks. The performance of other models downstream in the computational process highly …”
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Convolutional Autoencoder Model for Finger-Vein Verification von Hou, Borui, Yan, Ruqiang

“… This paper presents a novel deep learning-based method that integrates a Convolutional Auto-Encoder (CAE) with support vector machine (SVM) for finger-vein …”
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Multitask Autoencoder Model for Recovering Human Poses von Yu, Jun, Hong, Chaoqun, Rui, Yong, Tao, Dacheng

“… Human pose recovery in videos is usually conducted by matching 2-D image features and retrieving relevant 3-D human poses. In the retrieving process, the …”
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TrajVAE: A Variational AutoEncoder model for trajectory generation von Chen, Xinyu, Xu, Jiajie, Zhou, Rui, Chen, Wei, Fang, Junhua, Liu, Chengfei

“… Large-scale trajectory dataset is always required for self-driving and many other applications. In this paper, we focus on the trajectory generation problem, …”
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Inferring gene regulatory network from single-cell transcriptomes with graph autoencoder model von Wang, Jiacheng, Chen, Yaojia, Zou, Quan

“… Then it utilizes a graph autoencoder model to embed the global regulatory information contained in the graph …”
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Multitask Air-Quality Prediction Based on LSTM-Autoencoder Model von Xu, Xinghan, Yoneda, Minoru

“… With the development of the data-driven modeling techniques, using the neural network to simulate the transport process of atmospheric pollutants and …”
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Unsupervised Deep Learning based Variational Autoencoder Model for COVID-19 Diagnosis and Classification von Mansour, Romany F., Escorcia-Gutierrez, José, Gamarra, Margarita, Gupta, Deepak, Castillo, Oscar, Kumar, Sachin

“… •Employ an Unsupervised Variational Autoencoder Model for classification process•Validate the classification performance on COVID Chest X-ray dataset At present times …”
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druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico von Kadurin, Artur, Nikolenko, Sergey, Khrabrov, Kuzma, Aliper, Alex, Zhavoronkov, Alex

“… Deep generative adversarial networks (GANs) are the emerging technology in drug discovery and biomarker development. In our recent work, we demonstrated a …”
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Graph convolutional autoencoder model for the shape coding and cognition of buildings in maps von Yan, Xiongfeng, Ai, Tinghua, Yang, Min, Tong, Xiaohua

“… The shape of a geospatial object is an important characteristic and a significant factor in spatial cognition. Existing shape representation methods for …”
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Hourly PM2.5 concentration forecast using stacked autoencoder model with emphasis on seasonality von Bai, Yun, Li, Yong, Zeng, Bo, Li, Chuan, Zhang, Jin

“… Considering strong seasonal variation in meteorological conditions, in this paper, a seasonal stacked autoencoder model combining seasonal analysis and deep feature learning is proposed for forecasting the hourly PM …”
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A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis von Lin, Eugene, Mukherjee, Sudipto, Kannan, Sreeram

“… Background Single-cell RNA sequencing (scRNA-seq) is an emerging technology that can assess the function of an individual cell and cell-to-cell variability at …”
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SFGAE: a self-feature-based graph autoencoder model for miRNA–disease associations prediction von Ma, Mingyuan, Na, Sen, Zhang, Xiaolu, Chen, Congzhou, Xu, Jin

“… In this study, we resolve this issue by a novel self-feature-based graph autoencoder model, shortened as SFGAE …”
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An extended autoencoder model for reaction coordinate discovery in rare event molecular dynamics datasets von Frassek, M, Arjun, A, Bolhuis, P G

“… The reaction coordinate (RC) is the principal collective variable or feature that determines the progress along an activated or reactive process. In a …”
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An improved ensemble fusion autoencoder model for fault diagnosis from imbalanced and incomplete data von Yang, Jing, Xie, Guo, Yang, Yanxi

“… Skewed distribution and incompleteness of monitored data might cause feature submergence and information loss, rendering the fault diagnosis from imbalanced …”
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Motion Artifact Removal in Functional Near‐Infrared Spectroscopy Based on Long Short‐Term Memory‐Autoencoder Model von Yang, Pan, Wang, Junhong, Wang, Ting, Li, Lihua, Xu, Dongjuan, Xi, Xugang

“… ABSTRACT Motion artifact removal is a critical issue in functional near‐infrared spectroscopy (fNIRS) analysis tasks, with traditional methods relying heavily …”
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Improved Autoencoder Model With Memory Module for Anomaly Detection von Huang, Wei, Liu, Zhen, Jin, Xiaohang, Xu, Jinshan, Yao, Xinwei

“… As a commonly used model for anomaly detection, the autoencoder model for anomaly detection does not train the objective for extracted features, which is a downside of autoencoder model …”
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Optimized Deep Autoencoder Model for Internet of Things Intruder Detection von Lahasan, Badr, Samma, Hussein

“… To achieve this objective, an efficient two-layer optimizer is used to evolve a lightweight deep autoencoder model by performing simultaneous selection for the input features, the training instances …”
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scCompressSA: dual-channel self-attention based deep autoencoder model for single-cell clustering by compressing gene–gene interactions von Zhang, Wei, Yu, Ruochen, Xu, Zeqi, Li, Junnan, Gao, Wenhao, Jiang, Mingfeng, Dai, Qi

“… Background Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases. Due to …”
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Unveiling complex brain dynamics during movie viewing via deep recurrent autoencoder model von Wang, Kexin, Song, Limei, Li, Zhaowei, Wang, Liting, He, Xiaowei, Ren, Yudan, Lv, Jinglei

“… •Leveraging naturalistic fMRI, we characterize the dynamic, complex interactions among large-scale brain networks during the viewing of emotionally charged …”
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Calibrated reconstruction based adversarial autoencoder model for novelty detection von Huang, Yi, Li, Ying, Jourjon, Guillaume, Seneviratne, Suranga, Thilakarathna, Kanchana, Cheng, Adriel, Webb, Darren, Xu, Richard Yi Da

“… •Propose a unified model framework for location agnostic outlier detection.•Integrate implicit/explicit confidence calibration into a reconstruction based …”
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