Search Results - Convolutional autoen-coder~

Deep Learning Approach for Epileptic Focus Localization by Daoud, Hisham, Bayoumi, Magdy

“… Our first proposed method is based on semi-supervised learning, in which a deep convolutional autoencoder is trained and then the pre-trained encoder is used with multi-layer perceptron as a classifier…”
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Unsupervised Convolutional Autoencoder-Based Feature Learning for Automatic Detection of Plant Diseases by Pardede, Hilman F., Suryawati, Endang, Sustika, Rika, Zilvan, Vicky

“… In this paper, we present an unsupervised feature learning algorithm using the convolutional autoencoder for detection of plant diseases…”
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A Method for Power Flow Estimation in Power Systems with Incomplete Data by He, Xuzhong, Yin, Yushan, Wang, Yuhong, Zheng, Zongsheng, Zhou, Xu

“… This paper proposes a convolutional autoencoder model to enhance power flow estimation in power systems…”
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Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features by Liu, Bin, Li, Xiaofeng, Zheng, Gang

“… In order to liberate the DL-based inundation mapping from human supervision, we propose to use the clustering of deep convolutional autoencoder-generated features…”
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Clustering Continuous Wavelet Transform Characteristics of Heart Rate Variability through Unsupervised Learning by Wachowiak, Mark P., Moggridge, Jason J., Wachowiak-Smolikova, Renata

“… Among the applications of unsupervised learning, clustering is one of the most important. In this paper, an unsupervised autoen-coder architecture, deep…”
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Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper) by Alam, Mahabubul, Kundu, Satwik, Topaloglu, Rasit Onur, Ghosh, Swaroop

“…). Quantum machine learning (QML) has the potential to revolutionize image classification. In any typical DL-based image classification, we use convolutional neural network (CNN…”
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Objective Image Quality Analysis of Convolutional Neural Network Light Field Coding by Medda, Daniele, Song, Wei, Perra, Cristian

“… This paper presents the study of the performance of a convolutional neural network autoencoder as a tool for digital light field image compression…”
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Matrix Completion with Variational Graph Autoencoders: Application in Hyperlocal Air Quality Inference by Do, Tien Huu, Minh Nguyen, Duc, Tsiligianni, Evaggelia, Aguirre, Angel Lopez, Panzica La Manna, Valerio, Pasveer, Frank, Philips, Wilfried, Deligiannis, Nikos

“… We formulate air quality inference in this setting as a graph-based matrix completion problem and propose a novel variational model based on graph convolutional autoencoders…”
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Whole Heart Segmentation Using 3D FM-Pre-ResNet Encoder–Decoder Based Architecture with Variational Autoencoder Regularization by Habijan, Marija, Galić, Irena, Leventić, Hrvoje, Romić, Krešimir

“… Nowadays, convolutional neural networks (CNNs) emerged as a robust approach for medical image segmentation…”
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A Novel Hybrid Attentive Convolutional Autoencoder (HACA) Framework for Enhanced Epileptic Seizure Detection by Vaddi, Venkata Narayana, Sikha, Madhu Babu, Kodali, Prakash

“… This study presents a Hybrid Attentive Convolutional Autoen-coder (HACA) framework designed to address challenges in EEG signal processing for seizure detection…”
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SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints by Li, Yahang, Wang, Zepeng, Lam, Fan

“…) data by integrating learned nonlinear low-dimensional model and spatial constraints. A deep complex convolutional autoencoder (DCCAE…”
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Generating Synthetic Short-Range FMCW Range-Doppler Maps Using Generative Adversarial Networks and Deep Convolutional Autoencoders by de Oliveira, Marcio L. Lima, Bekooij, Marco J. G.

“…In this paper, we discuss the usage of Generative Adversarial Networks (GANs) and Deep Convolutional Autoen-coders (CAE…”
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Restoration of Historical Document Images Using Convolutional Neural Networks by Raha, Poulami, Chanda, Bhabatosh

“… In this research work, we have proposed a novel methodology using a single convolutional neural network to denoise and restore old handwritten documents…”
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Health indicator construction and status assessment of rotating machinery by spatio-temporal fusion of multi-domain mixed features by Duan, Yong, Cao, Xiangang, Zhao, Jiangbin, Xu, Xin

“…•An integrated HI model is constructed by taking advantage of SA, LSTM, and ICAE.•RS is used to exact the multi-domain features of the Fourier transformed…”
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DFD-SS: Document Forgery Detection using Spectral – Spatial Features for Hyperspectral Images by Jaiswal, Garima, Sharma, Arun, Kumar Yadav, Sumit

“…In the present era of machines and edge-cutting technologies, still document frauds persist. They are done intuitively by using almost identical inks, that it…”
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Deep Learning Anomaly Detection methods to passively detect COVID-19 from Audio by Murthy, Shreesha Narasimha, Agu, Emmanuel

“…The world has been severely affected by COVID-19, an infectious disease caused by the SARS-Cov-2 coronavirus. COVID-19 incubates in a patient for 7 days before…”
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Recurrent Nerual Imaging: An Evolutionary Approach for Mixed Possion-Gaussian Image Denoising by Ranganath, Aditya, DeGuchy, Omar, Santiago, Fabian, Singhal, Mukesh, Marcia, Roummel

“… Numerical experiments demonstrate that our proposed RNN approach outperforms convolutional autoen-coder methods for denoising and upsampling low-resolution images…”
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Denoising Method for Wireless Communication Signals Based on Convolutional AutoEncoder by Min, Woonggyu, Kim, Jongseok, Jo, Ohyun

“…In this paper, we propose a method to effectively remove noise from signals by utilizing convolutional autoen-coder…”
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AI based Segmented Anomaly Detection by Raj, Kiran S, Kumar, Priyanka

“… of detecting anomalies in a particular environment. The system elaborates on leveraging the power of convolutional autoencoders, LSTMs to detect anomalies of various kinds…”
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Enhancing Image Security Using DNA and Deep Steganography by K K, Mafnitha, K B, Anju

“… In order to solve the above described problems, this project provide a novel encryption method for color pictures that utilizes convolutional autoen- coder, DNA and steganography…”
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