Výsledky vyhledávání - "deep autoencoder network"

Recognition of geochemical anomalies using a deep autoencoder network Autor Xiong, Yihui, Zuo, Renguang

“… The southwestern Fujian district (China) is chosen as a case study area. A variety of learning rates, iterations, and the size of each hidden layer are constructing and training the deep autoencoder networks on all the geochemical samples…”
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Orthogonal Nonnegative Matrix Factorization using a novel deep Autoencoder Network Autor Yang, Mingming, Xu, Songhua

“…Orthogonal Nonnegative Matrix Factorization (ONMF) offers an important analytical vehicle for addressing many problems. Encouraged by record-breaking successes…”
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Infomax-based deep autoencoder network for recognition of multi-element geochemical anomalies linked to mineralization Autor Esmaeiloghli, Saeid, Tabatabaei, Seyed Hassan, Carranza, Emmanuel John M.

“…In recent years, deep autoencoder networks (DANs) have shown enormous potential to achieve state-of-the-art performance for recognizing multi-element geochemical anomalies related to mineralization…”
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A deep autoencoder network connected to geographical random forest for spatially aware geochemical anomaly detection Autor Soltani, Zeinab, Hassani, Hossein, Esmaeiloghli, Saeid

“…-stationarities in support of spatially aware anomaly detection. A deep autoencoder network (DAN) is trained to abstract deep feature codings…”
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Social movie recommender system based on deep autoencoder network using Twitter data Autor Tahmasebi, Hossein, Ravanmehr, Reza, Mohamadrezaei, Rezvan

“…Recommender systems attempt to provide effective suggestions to each user based on their interests and behaviors. These recommendations usually match the…”
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OutlierNets: Highly Compact Deep Autoencoder Network Architectures for On-Device Acoustic Anomaly Detection Autor Abbasi, Saad, Famouri, Mahmoud, Shafiee, Mohammad Javad, Wong, Alexander

“…Human operators often diagnose industrial machinery via anomalous sounds. Given the new advances in the field of machine learning, automated acoustic anomaly…”
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A Novel Lane-Changing Decision Model for Autonomous Vehicles Based on Deep Autoencoder Network and XGBoost Autor Gu, Xinping, Han, Yunpeng, Yu, Junfu

“…Lane-changing (LC) is a critical task for autonomous driving, especially in complex dynamic environments. Numerous automatic LC algorithms have been proposed…”
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An end-to-end framework for flight trajectory data analysis based on deep autoencoder network Autor Zhang, Weining, Hu, Minghua, Du, Jinghan

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Quality assessment of building footprint data using a deep autoencoder network Autor Xu, Yongyang, Chen, Zhanlong, Xie, Zhong, Wu, Liang

“…Volunteered geographic information (VGI), OpenStreetMap (OSM), has been used in many applications, especially when official spatial data are unavailable or…”
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Novelty Detection and Fault Diagnosis Method for Bearing Faults Based on the Hybrid Deep Autoencoder Network Autor Zhao, Yuanyuan, Hao, Huijuan, Chen, Yu, Zhang, Yu

“… based on a hybrid deep autoencoder network. Firstly, a hybrid deep autoencoder network with one input and two outputs was constructed…”
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Circuit reliability prediction based on deep autoencoder network Autor Xiao, Jie, Ma, Weifeng, Lou, Jungang, Jiang, Jianhui, Huang, Yujiao, Shi, Zhanhui, Shen, Qing, Yang, Xuhua

“…As semiconductor feature size continues to decrease and the density of integration continues to increase, highly reliable circuit design is experiencing many…”
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A Novel PAPR Reduction Scheme Based on Deep Autoencoder Network for FBMC Systems Autor Cheng, Xing, Chen, Deli, Li, Shuaishuai, He, Shanbao, Kong, Dejin

“…Filter bank multicarrier (FBMC) is a crucial complementary waveform to orthogonal frequency-division multiplexing (OFDM) in future communication systems…”
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DAE-TPGM: A deep autoencoder network based on a two-part-gamma model for analyzing single-cell RNA-seq data Autor Zhao, Shuchang, Zhang, Li, Liu, Xuejun

“… We introduced a deep autoencoder network based on a two-part-gamma model (DAE-TPGM…”
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Hybrid deep autoencoder network based adaptive cross guided bilateral filter for motion artifacts correction and denoising from MRI Autor Samuel, Shiju, Ochawar, Rohini S., Rukmini, M.S.S.

“…Removal of motion artifacts from medical images is essential, because the respiration by patient causes degradation in artifact removal. Therefore, getting an…”
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Performance Evaluation of Deep Autoencoder Network for Speech Emotion Recognition Autor AndleebSiddiqui, Maria, Hussain, Wajahat, Abbas, Syed, -, Danish-ur-Rehman

“…The learning methods with multiple levels of representation is called deep learning methods. The composition of simple but now linear modules results in…”
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A Design of Intrusion Detection using Modified Bat Algorithm and Deep Autoencoder Network Autor M.E., Soundari D.V, R, Kuralarasi, S, Kalieshwari, M, Kanimozhi, N, Kanimozhi

“…In this world, Intrusion Detection is more popular for preparing the network security systems. In current trend of increasing security system, there is a…”
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DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing Autor Su, Yuanchao, Li, Jun, Plaza, Antonio, Marinoni, Andrea, Gamba, Paolo, Chakravortty, Somdatta

“… In this paper, we develop a new technique for unsupervised unmixing which is based on a deep autoencoder network (DAEN…”
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Proximal Mapping-Incorporated Deep Autoencoder Network with Momentum Acceleration Method for Image Denoising Autor Zhao, Yang, Li, Ming, Huang, Meng, Zang, Qiyan, Wang, Lele, Zhang, Jian, Zhang, Heng

“… It adopts threefold ideas: 1) a deep autoencoder network that fully extracting latent features for precise reconstruction; 2…”
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Enhanced Short-Term GHI Prediction using Cloud-Aware Deep Autoencoder Network Autor N, Kalpalathika, Salih, Jumin, P, Lakshmi, Siddiqi, Nihal, A, Bhuvaneswari

“…Accurate short-term prediction of Global Horizontal Irradiance (GHI) is vital for reliable solar energy integration. This paper proposes a site-specific,…”
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A novel deep quantile matrix completion model for top-N recommendation Autor Yang, Mingming, Xu, Songhua

“…Matrix completion models have been receiving keen attention due to their wide applications in science and engineering. However, the majority of these models…”
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