Výsledky vyhledávání - supervised autoencoder

Predicting non-linear stress–strain response of mesostructured cellular materials using supervised autoencoder Autor 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…”
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Bagging Supervised Autoencoder Classifier for credit scoring Autor Abdoli, Mahsan, Akbari, Mohammad, Shahrabi, Jamal

“… To mitigate these challenges, in this paper, we propose the Bagging Supervised Autoencoder Classifier (BSAC…”
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Semi‐supervised deep autoencoder for seismic facies classification Autor Liu, Xingye, Li, Bin, Li, Jingye, Chen, Xiaohong, Li, Qingchun, Chen, Yangkang

“…‐supervised deep autoencoder by taking the mean of intra‐class and the whole population of facies into account to construct a classification regularization term, thereby improving the classification accuracy…”
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Pulmonary nodule diagnosis using dual‐modal supervised autoencoder based on extreme learning machine Autor Qiang, Yan, Ge, Lei, Zhao, Xin, Zhang, Xiaolong, Tang, Xiaoxian

“…‐modal deep supervised autoencoder based on extreme learning machine for which discriminative features are automatically learnt from the input data…”
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A Supervised Variational Autoencoder for Incomplete Multi‐View Classification Autor Xu, Yi, Chen, Anchi

“… Specifically, we design a supervised multi‐view variational autoencoder for missing view completion, which involves a Product of Experts (PoE…”
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A semi-supervised autoencoder for autism disease diagnosis Autor Yin, Wutao, Li, Longhai, Wu, Fang-Xiang

“… In this paper, we proposed a semi-supervised autoencoder (AE) for autism diagnosis using functional connectivity (FC…”
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Improved semi-supervised autoencoder for deception detection Autor Fu, Hongliang, Lei, Peizhi, Tao, Huawei, Zhao, Li, Yang, Jing

“… To solve this problem, this paper proposes a semi-supervised additive noise autoencoder model for deception detection…”
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Novel Stacked Input-Enhanced Supervised Autoencoder Integrated With Gated Recurrent Unit for Soft Sensing Autor 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…”
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Self-supervised Variational Autoencoder for Unsupervised Object Counting from Very High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas Autor Gella, Getachew Workineh, Gangloff, Hugo, Wendt, Lorenz, Tiede, Dirk, Lang, Stefan

“…In supervised learning, deep learning models demand a large corpus of annotated data for object detection and classification tasks…”
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Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum Autor 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…”
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A Semi-Supervised Autoencoder-Based Approach for Protein Function Prediction Autor Dhanuka, Richa, Tripathi, Anushree, Singh, Jyoti P.

“… A set of autoencoders is trained in a semi-supervised manner with protein sequences. Each autoencoder corresponds to a single protein function…”
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Single Sample Face Recognition via Learning Deep Supervised Autoencoders Autor Gao, Shenghua, Zhang, Yuting, Jia, Kui, Lu, Jiwen, Zhang, Yingying

“… Motivated by the success of deep learning in image representation, we propose a supervised autoencoder, which is a new type of building block for deep architectures…”
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A personalized classification model using similarity learning via supervised autoencoder Autor Jo, Hyunjae, Jun, Chi-Hyuck

“… through a supervised autoencoder and calculates the similarity measure between observations in the transformed latent space…”
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Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder Autor 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…”
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Forward and inverse design of kirigami via supervised autoencoder Autor 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…”
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scSSA: A clustering method for single cell RNA-seq data based on semi-supervised autoencoder Autor 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…”
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A New Semi-Supervised Classification Method Using a Supervised Autoencoder for Biomedical Applications Autor Gille, Cyprien, Guyard, Frederic, Barlaud, Michel

“… In this paper, we present a new approach to solve semi-supervised classification tasks for biomedical applications, involving a supervised autoencoder network…”
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Context Autoencoder for Self-supervised Representation Learning Autor Chen, Xiaokang, Ding, Mingyu, Wang, Xiaodi, Xin, Ying, Mo, Shentong, Wang, Yunhao, Han, Shumin, Luo, Ping, Zeng, Gang, Wang, Jingdong

“…We present a novel masked image modeling (MIM) approach, context autoencoder (CAE), for self-supervised representation pretraining…”
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Synthetic Aperture Local Conformal Autoencoder for Semi-Supervised Speaker's DOA Tracking Autor Cohen, Idan, Gannot, Sharon, Lindenbaum, Ofir

“… We aim to achieve this in real-time, using as few measurements as possible. Toward this goal, we present a semi-supervised learning scheme that tracks the speaker using acoustic features…”
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Fishing Gear Pattern Recognition by Including Supervised Autoencoder Dimensional Reduction Autor 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…”
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