Suchergebnisse - "Autoencoder framework"

Transformer-Based Autoencoder Framework for Nonlinear Hyperspectral Anomaly Detection von Wu, Ziyu, Wang, Bin

“… Recently, the autoencoder (AE) has received significant attention in the hyperspectral anomaly detection task. However, all existing AE-based anomaly detectors …”
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An Autoencoder Framework With Attention Mechanism for Cross-Domain Recommendation von 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 von 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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A memory pool variational autoencoder framework for cross-domain recommendation von Yang, Jie, Zhu, Jianxiang, Ding, Xiaofeng, Peng, Yaxin, Zhang, Yangchun

“… Cross-domain recommendation (CDR) leverages knowledge from the source domain to make recommendations for the cold-start users in the target domain. On account …”
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PepVAE: Variational Autoencoder Framework for Antimicrobial Peptide Generation and Activity Prediction von Dean, Scott N., Alvarez, Jerome Anthony E., Zabetakis, Dan, Walper, Scott A., Malanoski, Anthony P.

“… New methods for antimicrobial design are critical for combating pathogenic bacteria in the post-antibiotic era. Fortunately, competition within complex …”
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A Twice Denoising Autoencoder Framework for Random Seismic Noise Attenuation von Liao, Zhangquan, Li, Yong, Xia, En, Liu, Yingtian, Hu, Rui

“… Many seismic denoising algorithms are easily trapped in the dilemma of signal leaking and noise remaining. However, between the two situations, more complex …”
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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 von 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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Autoencoder framework based on orthogonal projection constraints improves anomalies detection von 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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A Shallow Autoencoder Framework for Epileptic Seizure Detection in EEG Signals von 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. The signal …”
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Generating Accurate and Diverse Audio Captions Through Variational Autoencoder Framework von Zhang, Yiming, Du, Ruoyi, Tan, Zheng-Hua, Wang, Wenwu, Ma, Zhanyu

“… Generating both diverse and accurate descriptions is an essential goal in the audio captioning task. Traditional methods mainly focus on improving the accuracy …”
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ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction von 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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End-to-End Multi-Band Adaptive Optimization Autoencoder Framework for Bandwidth-Limited Optical Wireless Fronthaul von Wei, Yuan, Chen, Chaoxu, Yao, Li, Zhang, Haoyu, Liu, Yinjun, Li, Fujie, Li, Ziwei, Shen, Chao, Zhang, Junwen, Chi, Nan, Shi, Jianyang

“… In this paper, we propose a multi-band adaptive optimization autoencoder framework (MBAE) to achieve end-to-end (E2E …”
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BiAEImpute: a robust bidirectional autoencoder framework for High-fidelity dropout imputation in single-cell transcriptomics von Zhang, Yi, Liu, Xinyuan, Wang, Yin, Wang, Yu

“… Background Single-cell RNA sequencing (scRNA-seq) technology enables an in-depth understanding of cellular transcriptome heterogeneity and dynamics. However, a …”
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Spatialsmooth: a spatially-aware convolutional autoencoder framework for enhanced deconvolution of spatial transcriptomics data von Yang, Xiao, Xiang, Jinjin, Feng, Yanbin, Zhao, Yanfang, Li, Huamei, Chen, Xiaozhou

“… Spatial transcriptomics technologies have revolutionized our understanding of tissue heterogeneity by providing gene expression data with spatial context …”
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A Joint Multiscale Graph Attention and Classify-Driven Autoencoder Framework for Hyperspectral Unmixing von Cao, Feilong, Situ, Yujia, Ye, Hailiang

“… Deep learning has recently gained popularity in hyperspectral unmixing (HU) and typical methods involve convolutional neural network-based (CNN-based) and …”
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Adaptive Temperature-Driven Ternary Contrastive Autoencoder Framework for Hyperspectral Target Detection von Li, Jiaojiao, Liu, Hangyun, Xu, Haitao, Wang, Chengyuan, Li, Yunsong, Du, Qian

“… Hyperspectral target detection (HTD) is a critical task in remote sensing, where numerous deep learning (DL)-based methods have emerged for their powerful …”
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A deep autoencoder framework for discovery of metastable ensembles in biomacromolecules von Bandyopadhyay, Satyabrata, Mondal, Jagannath

“… Biomacromolecules manifest dynamic conformational fluctuation and involve mutual interconversion among metastable states. A robust mapping of their …”
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GTAE-IDS: Graph Transformer-Based Autoencoder Framework for Real-Time Network Intrusion Detection von Ghadermazi, Jalal, Hore, Soumyadeep, Shah, Ankit, Bastian, Nathaniel D.

“… Network intrusion detection systems (NIDS) utilize signature and anomaly-based methods to detect malicious activities within networks. Advances in machine …”
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Enhanced Adaptive Autoencoder Framework for Continuous Monitoring and Fault Management in Industrial Sensors von de Oliveira, Lincoln Moura, El Kattel, Menaouar Berrehil, de Souza Oliveira, Demercil, Vasquez, Juan C., Guerrero, Josep M., Antunes, Fernando Luiz Marcelo

“… Ensuring the reliability and safety of industrial processes requires robust monitoring systems capable of detecting and diagnosing issues in complex, dynamic, …”
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HN3S: A Federated AutoEncoder framework for Collaborative Filtering via Hybrid Negative Sampling and Secret Sharing von Zhang, Lu, Li, Guohui, Yuan, Ling, Ding, Xuanang, Rong, Qian

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