Search Results - Autoencoder framework*

ParkMAE: a cross-linguistic masked autoencoder framework for robust Parkinson's disease detection from speech by Ando, Angelika, Lesage, Adrien, De Gennes, Marc, Riad, Rachid

“… Our self-supervised masked autoencoder approach, pretrained on this multilingual corpus, demonstrates superior performance achieving 39…”
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Variational Autoencoder Framework for Hyperspectral Retrievals (Hyper-VAE) of Phytoplankton Absorption and Chlorophyll a in Coastal Waters for NASA's EMIT and PACE Missions by Lou, Jiadong, Liu, Bingqing, Xiong, Yuanheng, Zhang, Xiaodong, Yuan, Xu

“…Phytoplankton absorbs and scatters light in unique ways, subtly altering the color of water-changes that are often minor for human eyes to detect but can be…”
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GCMCDTI: Graph convolutional autoencoder framework for predicting drug-target interactions based on matrix completion by Li, Jing, Zhang, Chen, Li, Zhengwei, Nie, Ru, Han, Pengyong, Yang, Wenjia, Liao, Hongmei

“… We regard the association prediction between drugs and targets as link prediction and treat the process as matrix completion, and then a graph convolutional auto-encoder framework is employed…”
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GenoDrawing: An Autoencoder Framework for Image Prediction from SNP Markers by Jurado-Ruiz, Federico, Rousseau, David, Botía, Juan A., Aranzana, Maria José

“… This study introduces an autoencoder framework, GenoDrawing, for predicting and retrieving apple images from a low-depth single-nucleotide polymorphism (SNP…”
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CAD-Skin: A Hybrid Convolutional Neural Network–Autoencoder Framework for Precise Detection and Classification of Skin Lesions and Cancer by Khan, Abdullah, Sajid, Muhammad Zaheer, Khan, Nauman Ali, Youssef, Ayman, Abbas, Qaisar

“… neural networks and autoencoders to improve the classification efficiency of skin cancer…”
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Transformer-Based Autoencoder Framework for Nonlinear Hyperspectral Anomaly Detection by Wu, Ziyu, Wang, Bin

“…Recently, the autoencoder (AE) has received significant attention in the hyperspectral anomaly detection task…”
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An autoencoder-based recommendation framework toward cold start problem: An autoencoder-based recommendation framework by Zhou, Wang, Tian, Ying, Haq, Amin Ul, Ahmad, Sultan

“… To overcome this issue, this article proposes a novel autoencoder framework referred to as CSRec, which owns the merits of both neural networks and collaborative filtering…”
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An Autoencoder Framework With Attention Mechanism for Cross-Domain Recommendation by Zhong, Shi-Ting, Huang, Ling, Wang, Chang-Dong, Lai, Jian-Huang, Yu, Philip S.

“… Therefore, in this article, we propose a novel autoencoder framework with an attention mechanism (AAM…”
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Cross-modal autoencoder framework learns holistic representations of cardiovascular state by Radhakrishnan, Adityanarayanan, Friedman, Sam F., Khurshid, Shaan, Ng, Kenney, Batra, Puneet, Lubitz, Steven A., Philippakis, Anthony A., Uhler, Caroline

“… Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct data modalities and constructing a holistic representation of cardiovascular state…”
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PepVAE: Variational Autoencoder Framework for Antimicrobial Peptide Generation and Activity Prediction by Dean, Scott N., Alvarez, Jerome Anthony E., Zabetakis, Dan, Walper, Scott A., Malanoski, Anthony P.

“… Here, we report a peptide generation framework, PepVAE, based around variational autoencoder (VAE…”
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A memory pool variational autoencoder framework for cross-domain recommendation by Yang, Jie, Zhu, Jianxiang, Ding, Xiaofeng, Peng, Yaxin, Zhang, Yangchun

“…; and the indirect relationship between the user and items related to other users. In order to process these relationships, we propose a novel framework named Memory Pool Variational AutoEncoder (MPVAE…”
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A Twice Denoising Autoencoder Framework for Random Seismic Noise Attenuation by Liao, Zhangquan, Li, Yong, Xia, En, Liu, Yingtian, Hu, Rui

“… The framework consists of a denoising autoencoder (DAE) and data generator. The DAE attenuates random noise without ground truth and works with a vectoring patching technique to reduce time complexity…”
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A Shallow Autoencoder Framework for Epileptic Seizure Detection in EEG Signals by Khan, Gul Hameed, Khan, Nadeem Ahmad, Altaf, Muhammad Awais Bin, Abbasi, Qammer

“…This paper presents a trainable hybrid approach involving a shallow autoencoder (AE) and a conventional classifier for epileptic seizure detection…”
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Autoencoder framework based on orthogonal projection constraints improves anomalies detection by Yu, Qien, Kavitha, Muthusubash, Kurita, Takio

“…In this study, we propose a novel autoencoder framework based on orthogonal projection constraint (OPC…”
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ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction by Jiang, Xinqing, Chen, Xiaojun, Xu, Lifeng, Zhang, Feng, Chen, Jiawei, Zhang, Wenqian

“…Small nucleolar RNAs (snoRNAs), a class of non-coding RNAs broadly distributed in eukaryotes, are emerging as pivotal regulators in the field of epigenomics…”
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Generating Accurate and Diverse Audio Captions Through Variational Autoencoder Framework by Zhang, Yiming, Du, Ruoyi, Tan, Zheng-Hua, Wang, Wenwu, Ma, Zhanyu

“… In this work, we propose a new diverse audio captioning method based on a variational autoencoder structure, dubbed AC-VAE, aiming to achieve a better trade-off between the diversity and accuracy…”
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ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction by Jiang, Xinqing, Chen, Xiaojun, Xu, Lifeng, Zhang, Feng, Chen, Jiawei, Zhang, Wenqian

“…Small nucleolar RNAs (snoRNAs), a class of non-coding RNAs broadly distributed in eukaryotes, are emerging as pivotal regulators in the field of epigenomics…”
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Adaptive Temperature-Driven Ternary Contrastive Autoencoder Framework for Hyperspectral Target Detection by Li, Jiaojiao, Liu, Hangyun, Xu, Haitao, Wang, Chengyuan, Li, Yunsong, Du, Qian

“… To address the above issues, we propose an adaptive temperature-driven ternary contrastive autoencoder (ATTCA…”
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BiAEImpute: a robust bidirectional autoencoder framework for High-fidelity dropout imputation in single-cell transcriptomics by Zhang, Yi, Liu, Xinyuan, Wang, Yin, Wang, Yu

“… Methods We proposed a bidirectional autoencoder-based model (BiAEImpute) for dropout imputation in scRNA-seq dataset…”
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A Joint Multiscale Graph Attention and Classify-Driven Autoencoder Framework for Hyperspectral Unmixing by Cao, Feilong, Situ, Yujia, Ye, Hailiang

“… Therefore, this article develops a joint multiscale graph attention and classify-driven autoencoder (MSGA-CD) framework for HU…”
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