Search Results - denoising autoencoder optical images

A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images by Liu, Jia, Gong, Maoguo, Qin, Kai, Zhang, Puzhao

“…We propose an unsupervised deep convolutional coupling network for change detection based on two heterogeneous images acquired by optical sensors and radars on different dates…”
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Research on Reconstruction Method of Occluded Micro-Expressions Based on Quantized Denoising Autoencoder by LIU Hui, GUO Te, LIU Dong, LI Yingying

“… in achieving precise texture reconstruction. In addition, the models used in such reconstruction methods often involve symmetric autoencoders based on U-Net and Generative Adversarial Networks (GAN…”
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Autoencoder Image Denoising to Increase Optical Character Recognition Performance in Text Conversion by Alamsyah, Nur, Fauzan, Mohamad Nurkamal, Putrada, Aji Gautama, Pane, Syafrial Fachri

“… Our research aims to build an autoencoder for denoising text images and evaluate the OCR's performance in converting the denoised image into text…”
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Retinal Optical Coherence Tomography Image Denoising using Convolutional Autoencoder by Wahid, Md. Ferdous, Aowlad Hossain, A. B. M.

“… In this paper, we present convolutional autoencoder (CAE) architecture for denoising retinal OCT images that incorporates an encoder and a decoder…”
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All‐Optical Autoencoder Machine Learning Framework Using Linear Diffractive Processors by Feng, Peijie, Tan, Yong, Chong, Mingzhe, Li, Lintao, Zhang, Zongkun, Liu, Fubei, Wen, Yongzheng, Tan, Yunhua

“… capabilities and multifunctional integration of D2NNs. Here, an all‐optical autoencoder (OAE) framework is proposed that linearly encodes the input wavefield into a prior shape distribution in the diffractive latent space…”
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Denoising Autoencoder Self-Organizing Map (DASOM) by Ferles, Christos, Papanikolaou, Yannis, Naidoo, Kevin J.

“… A fundamental approach is the use of higher-level representations devised by restricted Boltzmann machines and (denoising) autoencoders…”
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Image processing with Optical matrix vector multipliers implemented for encoding and decoding tasks by Kim, Minjoo, Kim, Yelim, Park, Won Il

“… Furthermore, our approach supports noise reduction and optical image generation, enabling models such as denoising autoencoders, variational autoencoders, and generative adversarial networks…”
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SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising by Ghosh, Swarup Kr, Biswas, Biswajit, Ghosh, Anupam

“… This study represents a deep learning based approach to denoising images and restoring features using stack denoising convolutional autoencoder…”
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Signal‐to‐noise ratio enhancement for Raman spectra based on optimized Raman spectrometer and convolutional denoising autoencoder by Fan, Xian‐guang, Zeng, Yingjie, Zhi, Yu‐Liang, Nie, Ting, Xu, Ying‐jie, Wang, Xin

“…‐the‐shelf cylindrical lens. On the other side of the algorithm, a relevant automatic denoising method of convolutional denoising autoencoder (CDAE…”
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Point spread function modelling for wide-field small-aperture telescopes with a denoising autoencoder by Jia, Peng, Li, Xiyu, Li, Zhengyang, Wang, Weinan, Cai, Dongmei

“… In this paper, we propose the use of a denoising autoencoder, a type of deep neural network, to model the point spread function of wide-field small-aperture telescopes…”
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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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Contrast sensitivity functions in autoencoders by Li, Qiang, Gomez-Villa, Alex, Bertalmío, Marcelo, Malo, Jesús

“…Three decades ago, Atick et al. suggested that human frequency sensitivity may emerge from the enhancement required for a more efficient analysis of retinal images…”
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Photodiagnosis with deep learning: A GAN and autoencoder-based approach for diabetic retinopathy detection by GENCER, Kerem, GENCER, Gülcan, CERAN, Tuğçe Horozoğlu, BİLİR, Aynur ER, DOĞAN, Mustafa

“…•The dual-stage enhancement combining GANs and denoising autoencoders ensures high-quality synthetic and original retinal images by reducing noise and improving image clarity, thus delivering superior…”
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A Novel Stacked Denoising Autoencoder-Based Reconstruction Framework for Cerenkov Luminescence Tomography by Cao, Xin, Wei, Xiao, Yan, Feng, Wang, Lin, Su, Linzhi, Hou, Yuqing, Geng, Guohua, He, Xiaowei

“… Here, we proposed a novel reconstruction framework based on stacking denoising autoencoders (SDAE…”
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Transformer enhanced autoencoder rendering cleaning of noisy optical coherence tomography images by Ahmed, Hanya, Zhang, Qianni, Donnan, Robert, Alomainy, Akram

“… In this work, a region-based, deep-learning, denoising framework is proposed for adaptive cleaning of noisy OCT-acquired images…”
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Denoising-driven information extraction network (DENet) for Brillouin optical time-domain analyzer by Zhang, Zhihao, Zhu, Borong, Qian, Yuhao, Wang, Liang, Ma, Xiaole, Yu, Kuanglu

“…•DENet integrates denoising and information extraction for BOTDA, enabling real-time processing…”
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Autoencoder-based dense denoiser and block-based wiener filter for noise reduction of optical coherence tomography by Juneja, Mamta, Chhatwal, Gurunameh Singh, Bhattacharya, Shatabarto, Thakur, Niharika, Jindal, Prashant

“…•Optical coherence tomography, an imaging modality used for diagnosis of retinal diseases…”
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Offline Urdu Nastaleeq Optical Character Recognition Based on Stacked Denoising Autoencoder by Ahmad, Ibrar, Wang, Xiaojie, Li, Ruifan, Rasheed, Shahid

“… Most of the prevalent Urdu Nastaleeq test recognition was trained and tested on small sets. This paper proposes the use of stacked denoising autoencoder for automatic feature extraction directly from raw pixel values of ligature images…”
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An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces by Mei, Shuang, Yang, Hua, Yin, Zhouping

“… This approach is carried out by reconstructing image patches with convolutional denoising autoencoder networks at different Gaussian pyramid levels, and synthesizing detection results…”
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Semisupervised learning using denoising autoencoders for brain lesion detection and segmentation by Alex, Varghese, Vaidhya, Kiran, Thirunavukkarasu, Subramaniam, Kesavadas, Chandrasekharan, Krishnamurthi, Ganapathy

“…The work explores the use of denoising autoencoders (DAEs) for brain lesion detection, segmentation, and false-positive reduction…”
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