Výsledky vyhledávání - Unsupervised autoencoder model

Variational autoencoder: An unsupervised model for encoding and decoding fMRI activity in visual cortex Autor Han, Kuan, Wen, Haiguang, Shi, Junxing, Lu, Kun-Han, Zhang, Yizhen, Fu, Di, Liu, Zhongming

“… Here, we explored an alternative deep neural network, variational auto-encoder (VAE), as a computational model of the visual cortex…”
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Model Inspired Autoencoder for Unsupervised Hyperspectral Image Super-Resolution Autor Liu, Jianjun, Wu, Zebin, Xiao, Liang, Wu, Xiao-Jun

“… The commonly used model-based approaches are unsupervised and flexible but rely on handcrafted priors…”
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Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model Autor Su, Lingtao, Xu, Chunhui, Zeng, Shuai, Su, Li, Joshi, Trupti, Stacey, Gary, Xu, Dong

“…) model to map gene expressions into a latent space and adapted a standard unsupervised autoencoder (AE…”
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An Elliptic Kernel Unsupervised Autoencoder-Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing Autor Alfaro-Mejia, Estefania, Delgado, Carlos J., Manian, Vidya

“… This article introduces the autoencoder graph ensemble model (AEGEM), a novel ensemble-based framework designed to enhance performance in both endmember extraction and abundance estimation…”
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Unsupervised transfer autoencoder model based on adversarial strategy for non-linear process monitoring Autor Yang, Xu, Xiao, Jieshi, Huang, Jian, Peng, Kaixiang

“… In this study, an unsupervised transfer autoencoder model based on adversarial strategy is proposed to address the issue of model mismatch and to extract universal features…”
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High-Fidelity Monocular Face Reconstruction Based on an Unsupervised Model-Based Face Autoencoder Autor Tewari, Ayush, Zollhofer, Michael, Bernard, Florian, Garrido, Pablo, Kim, Hyeongwoo, Perez, Patrick, Theobalt, Christian

“…In this work, we propose a novel model-based deep convolutional autoencoder that addresses the highly challenging problem of reconstructing a 3D human face from a single in-the-wild color image…”
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Ensemble unsupervised autoencoders and Gaussian mixture model for cyberattack detection Autor An, Peng, Wang, Zhiyuan, Zhang, Chunjiong

“… This paper proposes to use unsupervised ensemble autoencoders connected to the Gaussian mixture model (GMM…”
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Unsupervised Deep Learning based Variational Autoencoder Model for COVID-19 Diagnosis and Classification Autor 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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AN EXPLAINABLE CONVOLUTIONAL AUTOENCODER MODEL FOR UNSUPERVISED CHANGE DETECTION Autor Bergamasco, L., Saha, S., Bovolo, F., Bruzzone, L.

“… In this paper, we propose an explainable convolutional autoencoder model for CD. The model is trained in: 1…”
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Colour‐patterned fabric defect detection based on an unsupervised multi‐scale U‐shaped denoising convolutional autoencoder model Autor Zhang, Hongwei, Liu, Shuting, Tan, Quanlu, Lu, Shuai, Yao, Le, Ge, Zhiqiang

“…This study proposes an unsupervised, learning‐based, reconstructed scheme and a residual analysis…”
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Unsupervised Dual Convolutional Autoencoder Models for Efficient Group Anomaly Detection of HST Bogies via Domain Adversarial Learning Autor Chang, Yuanhong, Zhong, Shuncong, Pan, Tongyang, Xie, Jingsong

“… Hence, this paper proposes a dual convolutional autoencoder (d-CAE) network combined with unsupervised domain-adversarial learning for group anomaly detection of bogies…”
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MoFA: Model-Based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction Autor Tewari, Ayush, Zollhofer, Michael, Hyeongwoo Kim, Garrido, Pablo, Bernard, Florian, Perez, Patrick, Theobalt, Christian

“…In this work we propose a novel model-based deep convolutional autoencoder that addresses the highly challenging problem of reconstructing a 3D human face from a single in-the-wild color image…”
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A deep-learning-based unsupervised model on esophageal manometry using variational autoencoder Autor Kou, Wenjun, Carlson, Dustin A., Baumann, Alexandra J., Donnan, Erica, Luo, Yuan, Pandolfino, John E., Etemadi, Mozziyar

“…•Generative capability was compared among models with different latent space and loss.•Key motility patterns were found well-encoded by 4-dimensional latent variables…”
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3D CAD model retrieval based on sketch and unsupervised variational autoencoder Autor Qin, Feiwei, Qiu, Shi, Gao, Shuming, Bai, Jing

“… Hence it is difficult to meet the actual needs of the industry. In this paper, we propose a 3D CAD model retrieval approach that considers the speed, accuracy and ease of use at the same time, based on sketches and unsupervised learning…”
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Intrinsic Decomposition Model-Guided Two-Stream Coupled Autoencoder for Unsupervised Hyperspectral Image Change Detection Autor Sun, Jia, Liu, Jia, Xiao, Liang

“… Inspired by the intrinsic image decomposition, we propose a novel unsupervised deep-learning (DL…”
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Image Retrieval Using Convolutional Autoencoder, InfoGAN, and Vision Transformer Unsupervised Models Autor Sabry, Eman S., Elagooz, Salah S., El-Samie, Fathi E. Abd, El-Shafai, Walid, El-Bahnasawy, Nirmeen A., El-Banby, Ghada M., Algarni, Abeer D., Soliman, Naglaa F., Ramadan, Rabie A.

“…Query by Image Content (QBIC), subsequently known as Content-Based Image Retrieval (CBIR), offers an advantageous solution in a variety of applications,…”
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Identifying Individualized Functional Brain Networks: An Unsupervised Deep Temporal Attention Based Autoencoder Model Autor Wang, Kexin, Ren, Yudan, Liu, Zhengyang, Yin, Song, Ding, Zhenqing, Li, Xiao, He, Xiaowei

“… In this study, we proposed an unsupervised deep temporal attention based autoencoder model (DTA-AE) that aimed to model brain function in a compact, standardized latent space, thus representing complex brain activities via dense embedding vectors…”
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Autoencoders for unsupervised anomaly detection in high energy physics Autor Finke, Thorben, Krämer, Michael, Morandini, Alessandro, Mück, Alexander, Oleksiyuk, Ivan

“… We scrutinize the usage of autoencoders for unsupervised anomaly detection based on reconstruction loss to show their capabilities, but also their limitations…”
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Unsupervised learning with a physics-based autoencoder for estimating the thickness and mixing ratio of pigments Autor Shitomi, Ryuta, Tsuji, Mayuka, Fujimura, Yuki, Funatomi, Takuya, Mukaigawa, Yasuhiro, Morimoto, Tetsuro, Oishi, Takeshi, Takamatsu, Jun, Ikeuchi, Katsushi

“… This paper proposes an unsupervised autoencoder model for thickness and mixing ratio estimation…”
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Intelligent Monitoring Model for Lost Circulation Based on Unsupervised Time Series Autoencoder Autor Wu, Liwei, Wang, Xiaopeng, Zhang, Ziyue, Zhu, Guowei, Zhang, Qilong, Dong, Pinghua, Wang, Jiangtao, Zhu, Zhaopeng

“… To address these issues, this paper proposes an unsupervised time series autoencoder (BiLSTM-AE) intelligent monitoring model for lost circulation, aiming to overcome the limitations of supervised algorithms…”
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