Výsledky vyhledávání - "deep autoencoder network"

DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing Autor Su, Yuanchao, Li, Jun, Plaza, Antonio, Marinoni, Andrea, Gamba, Paolo, Chakravortty, Somdatta

“…Spectral unmixing is a technique for remotely sensed image interpretation that expresses each (possibly mixed) pixel as a combination of pure spectral…”
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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…”
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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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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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A deep autoencoder network connected to geographical random forest for spatially aware geochemical anomaly detection Autor Soltani, Zeinab, Hassani, Hossein, Esmaeiloghli, Saeid

“…Machine learning (ML) and deep learning (DL) techniques have recently shown encouraging performance in recognizing metal-vectoring geochemical anomalies within…”
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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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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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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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A Comparative Study of Sentiment-Aware Collaborative Filtering Algorithms for Arabic Recommendation Systems Autor Al-Ghuribi, Sumaia Mohammed, Mohd Noah, Shahrul Azman, Mohammed, Mawal A., Tiwary, Neeraj, Saat, Nur Izyan Yasmin

“…The rapid proliferation of online information necessitates efficient Recommendation Systems (RSs) to assist users in discovering relevant content. While…”
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Research on a Feature Enhancement Extraction Method for Underwater Targets Based on Deep Autoencoder Networks Autor Ji, Fang, Li, Guonan, Lu, Shaoqing, Ni, Junshuai

“…The low-frequency line spectrum of the radiated noise signals of hydroacoustic targets contains features describing the intrinsic properties of the target that…”
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Identification of Traffic Flow Spatio-Temporal Patterns and Their Associated Weather Factors: A Case Study in the Terminal Airspace of Hong Kong Autor Zhang, Weining, Pan, Weijun, Zhu, Xinping, Yang, Changqi, Du, Jinghan, Yin, Jianan

“…In this paper, a data-driven framework aimed at investigating how weather factors affect the spatio-temporal patterns of air traffic flow in the terminal…”
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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

“…In the field of image processing, autoencoder networks have emerged as potent approaches for image denoising. However, traditional autoencoder networks often…”
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Structure and Thrust Fault Detection and Diagnosis for Hypersonic Aircrafts via a Data-Driven Approach Autor Zhang, Chaoyue, Hu, Qinglei, Han, Tuo

“…As a complex and significant part of the hypersonic aircraft operating under high speeds and harsh flight conditions, its structure and thrust systems are…”
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A Tensor Solution for Health Indicator Construction of Metro Wheelset Degradation with Irregular Noise Autor Wang, Yu, Mao, Wentao, Kou, Linlin, Liu, Keying

“…During the operation of metro vehicles, wheel flange and wheel diameter continue to be abrased, so wheel degradation is inevitable. Influenced by the states of…”
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Spatial-Spectral Autoencoder Networks for Hyperspectral Unmixing Autor Huang, Yongfa, Li, Jie, Qi, Lin, Wang, Ying, Gao, Xinbo

“…We present a spatial-spectral autoencoder (SSAE) for hyperspectral unmixing, including a net for endmember extraction (EENet) and a net for abundance…”
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Geochemical anomaly recognition based on Gaussian mixture model Autor Wang, Haijun, Xue, Linfu, Ran, Xiangjin

“…In order to find the optimal method for identifying geochemical anomalies in geochemical exploration, the Gaussian mixture model and the deep autoencoder…”
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Modulation Recognition of Digital Signal Based on Deep Auto-Ancoder Network Autor Tu Ya, Yun Lin, Hui Wang

“…Automated Modulation Classification (AMC) shows great significance for any receiver that has little knowledge of the modulation scheme of the received signal…”
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Deep depth-based representations of graphs through deep learning networks Autor Bai, Lu, Cui, Lixin, Bai, Xiao, R. Hancock, Edwin

“…Graph-based representations are powerful tools in structural pattern recognition and machine learning. In this paper, we propose a framework of computing the…”
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A Framework For Network Intrusion Detection Based on Unsupervised Learning Autor Hui, Wang, Dongming, Wang, Dejian, Li, Lin, Zeng, Zhe, Wang

“…Anomaly detection is the primary method of detecting intrusion. Unsupervised models, such as auto-encoders network, auto-encoder, and GMM, are currently the…”
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Direction of Arrival Estimation by Using Deep Autoencoder Network Autor Nurbas, Ekin, Onat, Emrah

“…In this paper, an unique and innovative method which uses problem deep ecoder networks is proposed for the solution of arrival angle estimation problem. Also…”
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