Suchergebnisse - complex convolutional autoencoder

Domain-Adaptive Direction of Arrival (DOA) Estimation in Complex Indoor Environments Based on Convolutional Autoencoder and Transfer Learning von Shen, Lingyu, Li, Jianfeng, Pan, Jingjing, Shi, Junpeng, Xu, Rui, Wang, Hao, Deng, Weiming

“… The approach begins with deep feature extraction using a Convolutional Autoencoder (CAE) and employs a Domain-Adversarial Neural Network (DANN …”
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An Incipient Fault Diagnosis Method Based on Complex Convolutional Self-Attention Autoencoder for Analog Circuits von Gao, Tianyu, Yang, Jingli, Jiang, Shouda, Li, Ye

“… Consequently, a complex convolutional self-attention autoencoder (CCSAE) is proposed in this paper to perform incipient fault diagnosis for analog circuits, which contains …”
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Complex-Valued Convolutional Autoencoder and Spatial Pixel-Squares Refinement for Polarimetric SAR Image Classification von Shang, Ronghua, Wang, Guangguang, A. Okoth, Michael, Jiao, Licheng

“… In this work, a complex-valued convolutional autoencoder network (CV-CAE) is proposed. CV-CAE extends the encoding and decoding of CAE to complex domain so that the phase information can be adopted …”
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Compact representation and identification of important regions of metal microstructures using complex-step convolutional autoencoders von Arumugam, Dharanidharan, Kiran, Ravi

“… In this study, we propose a complex-step convolutional autoencoder to identify the regions that are important in a metal microstructure for compact representation and secure sharing …”
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Convolutional autoencoder based condition monitoring system for unique complex technical systems von Tahtali, Emre, Adamscheck, Marco, Overmeyer, Ludger, Wurz, Marc Christopher, Lotz, Christoph, Klaas, Daniel

“… This paper presents the development of a condition monitoring system for a unique, complex technical system represented by a drop tower …”
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Research on UAV Jamming Signal Generation Based on Intelligent Jamming von Xue, Haonan, Zhuo, Zhihai, Yan, Weihao, Zhang, Yuexia

“… Traditional communication jamming methods face several challenges. These include low efficiency, difficulties in managing dynamic and complex electromagnetic environments, and a heavy reliance on prior knowledge about the signals …”
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An Attention Based Complex-valued Convolutional Autoencoder for GEO SA-Bi SAR Ship Target Refocusing von Lian, Meng, Bolic, Miodrag

“… Inspired by the recent success of artificial neural network (ANN) and deep learning (DL) in optical image processing, an improved complex-valued convolutional autoencoder (ICV-CAE …”
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Deep-Learning-Based Dictionary Construction for MIMO Radar Detection in Complex Scenes von Wang, Hongyan, Zhou, He, Guo, Qinghua, Li, Jun

“… , where the nonlinear characteristics of the received signal are effectively represented and corrected using a complex-valued convolutional autoencoder (CVCAE) network …”
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Physiological Signal-Based Real-Time Emotion Recognition Based on Exploiting Mutual Information with Physiologically Common Features von Ean-Gyu Han, Tae-Koo Kang, Myo-Taeg Lim

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SAR Images Unsupervised Feature Abstraction with A Complex-valued Convolutional Autoencoder von He, Jinling, Jin, Yuhang, Tian, Sirui, Wang, Chao, Zhang, Hong

“… In order to solve these problems, this paper proposes a model for vehicle SAR image interpretation based on complex-valued convolutional auto-encoder (CV-CAE …”
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Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system von Teutsch, Philipp, Pfeffer, Philipp, Sharifi Ghazijahani, Mohammad, Cierpka, Christian, Schumacher, Jörg, Mäder, Patrick

“… Within the context of reduced-order models, convolutional autoencoders (CAEs) pose a universally applicable alternative to conventional approaches …”
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Convolutional Long Short-Term Memory Autoencoder-Based Feature Learning for Fault Detection in Industrial Processes von Yu, Jianbo, Liu, Xing, Ye, Lyujiangnan

“… This article proposes a new deep neural network (DNN), convolutional long short-term memory autoencoder (CLSTM-AE …”
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Optimal satellite selection using quantum convolutional autoencoder for low-cost GNSS receiver applications von Arasavali, Nalineekumari, Kumar, Mogadala Vinod, Gottapu, Sasibhushana Rao, Kumar, Om Prakash, Kakade, Priyanka Desai, Vincent, Shweta, Mane, Pallavi R., Kumar, Sachin

“… This work proposes the quantum convolutional autoencoder-based optimal satellite selection method …”
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Fast Full Wave Electromagnetic Forward Solver Based on Deep Conditional Convolutional Autoencoders von Zhang, Huan Huan, Yao, He Ming, Jiang, Lijun, Ng, Michael

“… This proposed fast full-wave solver for EMF process is designed based on the deep conditional convolutional autoencoder (DCCAE …”
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Population-based 3D respiratory motion modelling from convolutional autoencoders for 2D ultrasound-guided radiotherapy von Mezheritsky, Tal, Romaguera, Liset Vázquez, Le, William, Kadoury, Samuel

“… •Motion compensation model for free-breathing ultrasound-guided radiotherapy treatments.•A novel real-time motion modelling framework composed of a rigid …”
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Temporal convolutional denoising autoencoder network for air pollution prediction with missing values von Samal, K. Krishna Rani, Babu, Korra Sathya, Das, Santos Kumar

“… These issues make air quality models more complex and challenging to introspect. So, we developed Temporal Convolutional Denoising Autoencoder (TCDA …”
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Reconstructing Complex Cardiac Excitation Waves From Incomplete Data Using Echo State Networks and Convolutional Autoencoders von Herzog, Sebastian, Zimmermann, Roland S., Abele, Johannes, Luther, Stefan, Parlitz, Ulrich

“… , only. To bridge the gap between measurable and not measurable quantities we use two approaches from machine learning, echo state networks and convolutional autoencoders, to solve two relevant data …”
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Spindle Autoencoder-CNN hybrid model for cardiac arrhythmia classification von Akkuş, Merve, Karabatak, Murat, Tekin, Ramazan

“… ) with a Convolutional Neural Network (CNN). Unlike traditional autoencoders, the Spindle Autoencoder utilizes deeper and symmetric hidden layers to extract complex and meaningful representations from ECG signals …”
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Deep Convolutional Autoencoders for Robust Flow Model Calibration Under Uncertainty in Geologic Continuity von Jiang, Anyue, Jafarpour, Behnam

“… Subsurface flow model calibration is commonly performed by assuming that a known conceptual model of geologic continuity is available and can be used to …”
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Model order reduction of building energy simulation models using a convolutional neural network autoencoder von Banihashemi, Farzan, Weber, Manuel, Lang, Werner

“… This paper introduces a novel approach to model order reduction (MOR) of BES models. The approach utilizes a deep learning-based unsupervised convolutional neural network autoencoder (CNN-AE …”
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