Search Results - Sparse denoised autoencoder

Effective Flood prediction model based on Twitter Text and Image analysis using BMLP and SDAE-HHNN by Kamoji, Supriya, Kalla, Mukesh

“…In recent years, social media platforms such as Twitter have garnered a lot of interest as a new source of text data for quick flood awareness and effective…”
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Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks by Liu, Kai-Yuan, Li, Xing-Yu, Lai, Yu-Rui, Su, Hang, Wang, Jia-Chen, Guo, Chun-Xu, Xie, Hong, Guan, Ji-Song, Zhou, Yi

“… Inspired by recent advances in brain science, we propose the denoised internal models (DIM), a novel generative autoencoder-based model to tackle this challenge…”
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Improving brain MRI denoising using convolutional AutoEncoder and sparse representations by Velayudham, A, Madhan Kumar, K., Krishna Priya, MS

“… However, noise often degrades image quality, leading to inaccurate diagnoses. To address this issue, a Convolutional AutoEncoder-based Orthogonal Matching Pursuit (CAE-OMP…”
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A denoising method for ECG signals based on CEEMDAN-TSO and stacked sparse autoencoders by Li, Shun, Li, Juan, Mao, Jiandong, Hong, Wei, Sun, Ao

“…), Tuna Swarm Optimization (TSO), and Stacked Sparse Autoencoder (SSAE), named CEEMDAN-TSO-SSAE…”
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Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal‐to‐noise ratio and speed of MRS by Wang, Jing, Ji, Bing, Lei, Yang, Liu, Tian, Mao, Hui, Yang, Xiaofeng

“…Background While magnetic resonance imaging (MRI) provides high resolution anatomical images with sharp soft tissue contrast, magnetic resonance spectroscopy…”
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Denoising Autoencoder Aided Spectrum Reconstruction for Colloidal Quantum Dot Spectrometers by Zhang, Jinhui, Zhu, Xueyu, Bao, Jie

“… Specifically, we employ a denoising autoencoder, a machine-learning approach, to reduce noise in the filters' raw measurements before performing the reconstruction…”
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Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks by Liu, Kaiyuan, Li, Xingyu, Lai, Yurui, Zhang, Ge, Su, Hang, Wang, Jiachen, Guo, Chunxu, Guan, Jisong, Zhou, Yi

“… Inspired by recent advances in brain science, we propose the Denoised Internal Models (DIM), a novel generative autoencoder-based model to tackle this challenge…”
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A High-Generalization Variational Denoising Autoencoder for Micronewton Thrust Signal Noise Removal and Step Reconstruction by Chen, Xingyu, Zhao, Liye, Xu, Jiawen, Liu, Zhikang, Dai, Zhuoping, Xu, Luxiang, Guo, Ning, Zhang, Hong

“… In this study, we have developed a novel generative denoising method, named variational denoising autoencoder (VDAE…”
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Sparsity‐based autoencoders for denoising cluttered radar signatures by Ram, Shobha Sundar, Vishwakarma, Shelly, Sneh, Akanksha, Yasmeen, Kainat

“…‐dependent and target‐independent static and dynamic clutter arising from walls. A stacked and sparse denoising autoencoder (StackedSDAE…”
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Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders by Ibrahim, Muhammad, Hanif, Muhammad, Ahmad, Shabir, Jamil, Faisal, Sehar, Tayyaba, Lee, YunJung, Kim, DoHyeun

“… This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method…”
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Multi-lead model-based ECG signal denoising by guided filter by Hao, Huaqing, Liu, Ming, Xiong, Peng, Du, Haiman, Zhang, Hong, Lin, Feng, Hou, Zengguang, Liu, Xiuling

“… For each person, a patient-specific statistical model will be constructed by sparse autoencoder (SAE…”
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Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoder by Liu, Zhi-Song, Siu, Wan-Chi, Wang, Li-Wen, Li, Chu-Tak, Cani, Marie-Paule, Chan, Yui-Lam

“… Given that real images contain various noise and artifacts, we propose a joint image denoising and super-resolution model via Variational AutoEncoder…”
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Seismic noise attenuation by signal reconstruction: an unsupervised machine learning approach by Gao, Yang, Zhao, Pingqi, Li, Guofa, Li, Hao

“…ABSTRACT Random noise attenuation is an essential step in seismic data processing for improving seismic data quality and signal‐to‐noise ratio. We adopt an…”
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Data-Driven OTFS Channel Estimation Based on Gated Recurrent Convolutional Autoencoder by Chen, Junshen, Yuan, Qihao, Zhang, Shiyao, Liu, Chang

“… Due to sparse representation of the delay-Doppler (DD) domain, the related channel information can be estimated by means of the embedded pilot technique…”
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Sparsity Based Autoencoders for Denoising Cluttered Radar Signatures by Shobha Sundar Ram, Vishwakarma, Shelly, Akanksha Sneh, Kainat Yasmeen

“… A stacked and sparse denoising autoencoder (StackedSDAE) is proposed for mitigating wall clutter in indoor radar images…”
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Bearing Remaining Useful Life Prediction based on TSDAE and Pathformer-TCLSTM by Fu, Guanghua, Yang, Yujie, Liu, Yonghui, Wang, Xuegen

“… To address these problems, this paper proposes a RUL prediction approach mainly based on temporal sparse denoising autoencoders (TSDAE…”
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A Robust Speaker Identification Algorithm Based On Atomic Decomposition and Sparse Redundant Dictionary Learning by Bryan, Thomas James

“…Speaker identification is performed in high additive white Gaussian noise environments by processing sounds as images in the time-frequency plane. The…”
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COVID-19 CT image denoising algorithm based on adaptive threshold and optimized weighted median filter by Guo, Shuli, Wang, Guowei, Han, Lina, Song, Xiaowei, Yang, Wentao

“…CT image of COVID-19 is disturbed by impulse noise during transmission and acquisition. Aiming at the problem that the early lesions of COVID-19 are not…”
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A comparative case study between shallow and deep neural networks in induction motor's fault diagnosis by Gholaminejad, Azadeh, Jorkesh, Saeid, Poshtan, Javad

“…‐pump dry running disturbances is investigated. Easily available three‐phase electrical current signals are denoised using independent component analysis, and then the…”
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Improved PET Image Reconstruction Using Machine Learning Techniques by Yang, Bao

“…) regularizers may not distinguish true edges from noise in practice. We propose to use a superior denoiser, dictionary learning based sparse representation…”
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