Suchergebnisse - Convolution autoencoder

Accurate microwave filter design based on particle swarm optimization and one‐dimensional convolution autoencoders von Wang, Yanxing, Zhang, Zhuowei, Yi, Yaxin, Zhang, Yongliang

“… This paper proposes a one‐dimensional convolutional autoencoders (1D‐CAE) surrogate‐based electromagnetic …”
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Deep Self-Supervised Graph Attention Convolution Autoencoder for Networks Clustering von Chen, Chao, Lu, Hu, Hong, Haotian, Wang, Hai, Wan, Shaohua

“… To solve this problem, we propose a Deep Self-Supervised Attention Convolution Autoencoder Graph Clustering (DSAGC …”
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Fault Diagnosis in Centrifugal Pumps: A Dual-Scalogram Approach with Convolution Autoencoder and Artificial Neural Network von Zaman, Wasim, Ahmad, Zahoor, Kim, Jong-Myon

“… This paper proposes a new fault diagnosis method for centrifugal pumps by combining signal processing with deep learning techniques. Centrifugal pumps …”
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A hybrid deep learning-based fruit classification using attention model and convolution autoencoder von Xue, Gang, Liu, Shifeng, Ma, Yicao

“… chain, factories, supermarkets, and other fields. In this paper, we develop a hybrid deep learning-based fruit image classification framework, named attention-based densely connected convolutional networks with convolution autoencoder (CAE-ADN …”
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Self-Tuning Transfer Dynamic Convolution Autoencoder for Quality Prediction of Multimode Processes With Shifts von Yang, Chao, Liu, Qiang, Wang, Chen, Ding, Jinliang, Cheung, Yiu-ming

“… First, in order to capture domain-invariant spatiotemporal (DIST) features, a transfer dynamic convolution autoencoder (TDCAE …”
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DeepSORT with siamese convolution autoencoder embedded for honey peach young fruit multiple object tracking von Zhang, Tian, Zhao, Dongfang, Chen, Yesheng, Zhang, Hongli, Liu, Shulin

“… •A staged data preprocessing strategy for honey peach young fruit is designed.•The SCAE is proposed to ensure the discriminability of the extracted …”
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Convolution Autoencoder based Classification Model for Content Based Image Retrieval von Rai, Rishi, Sisodia, Dilip Singh

“… The Content Based Image Retrieval (CBIR) has gained significant importance due to surge of online images and its diverse applications. The CBIR system gets an …”
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STEAMCODER: Spatial and Temporal Adaptive Dynamic Convolution Autoencoder for Anomaly Detection von Xu, Peng, Gan, Honglu, Fu, Hua, Zhang, Zhongbao

“… Hence, an adaptive algorithm is required to address these problems. We design a novel algorithm called Spatial-TEmporal Adaptive dynaMic Convolution autoencODER for Anomaly Detection (STEAMCODER), specifically …”
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DeepShip: An underwater acoustic benchmark dataset and a separable convolution based autoencoder for classification von Irfan, Muhammad, Jiangbin, Zheng, Ali, Shahid, Iqbal, Muhammad, Masood, Zafar, Hamid, Umar

“… •Study of 6 T-F features by 8 machine learning and deep learning methods on dataset.•Proposed a separable convolutional autoencoder for better classification accuracy …”
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Fault Feature of Gearbox Vibration Signals Based on Morphological Filter Dynamic Convolution Autoencoder von Yu, Jianbo, Huang, Jiahuan, Liu, Changhui, Xia, Beixin

“… In this study, a new DNN, morphological filter dynamic convolutional autoencoder (MF-DCAE), is proposed for fault feature extraction from vibration signals …”
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Temporal denoising and deep feature learning for enhanced defect detection in thermography using stacked denoising convolution autoencoder von Yerneni, Naga Prasanthi, Ghali, V.S., Vesala, G.T., Wang, Fei, Mulaveesala, Ravibabu

“… •Temporal denoising of thermal profiles along with deep feature learning for enhanced defect detection in FMTWI is highlighted through a stacked denoising convolution autoencoder …”
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Anomaly detection based on temporal convolution Autoencoders von Wu, Lihao, Liang, Jiahui

“… And unsupervised detection of outliers in time series is a very challenging task. For most detection tasks of time series outliers, the autoencoder is one of the main choices …”
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Fabric Defect Detection Using a One-class Classification Based on Depthwise Separable Convolution Autoencoder von Chen, Chun, Deng, Xiaoyan, Yu, Zhuliang, Wu, Zhengtao

“… This paper proposes a method applying depthwise separable convolution autoencoder on dimensionality reduction and one-class classifier support vector data description (SVDD …”
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Video anomaly detection and localization via multivariate gaussian fully convolution adversarial autoencoder von Li, Nanjun, Chang, Faliang

“… Gaussian Fully Convolution Adversarial Autoencoder (MGFC-AAE), while the latent representations of anomalies …”
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Industrial Robot Vibration Anomaly Detection Based on Sliding Window One-Dimensional Convolution Autoencoder von Zhong, ZhiDan, Zhao, Yao, Yang, AoYu, Zhang, HaoBo, Qiao, DongHao, Zhang, ZhiHui

“… This study proposes Sliding Window One-Dimensional Convolutional Autoencoder (SW1DCAE), an unsupervised vibration anomaly detection algorithm for industrial robots …”
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SpAuCNN: Sparse autoencoder convolution neural network architecture for emotion recognition among intense level autism disorder hospitalized children von Bethineedi, Veerendra, Damodar, Ramakrishna

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Parametric Study of Convolution Autoencoder for Reduced-Order Modeling of Turbulent Flow von Beiki, Alireza, Kamali, Reza

“… In this paper, we analyze the capabilities of several multiscale convolutional autoencoder architectures for reduced-order modeling of two-dimensional unsteady turbulent flow over a cylinder …”
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Identifying Functional Brain Networks under Naturalistic Paradigm via A Three-Dimensional Spatial Attention Convolution Autoencoder von Ren, Yudan, Yin, Song, Liu, Zhengyang, Wang, Kexin, Le, Mingnan, Zhang, Wei, Li, Xiao

“… To address this, we propose a three-dimensional convolutional autoencoder network incorporating the Convolutional Block Attention Module (SA-3DCAE …”
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A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors von Toma, Rafia Nishat, Piltan, Farzin, Kim, Jong-Myon

“… Fault diagnosis and classification for machines are integral to condition monitoring in the industrial sector. However, in recent times, as sensor technology …”
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A Truth Inference Algorithm Using Bidirectional Convolution Autoencoder for Crowdsourcing Image Segmentation von Li, Yueyang, Dong, Zhaoan, Li, Guangshun, Wang, Sifeng, Wang, Xiaofan, Liu, Zhibin, Li, Zhenqiang, Wang, Boyong

“… In the paper, we propose a truth inference algorithm based on bidirectional convolutional autoencoder to capture and utilize the internal structure information underling complex tasks, e.g. image segmentation …”
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