Search Results - "convolutional autoen-coder"

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

“…The task of epileptic focus localization receives great attention due to its role in an effective epileptic surgery. The clinicians highly depend on the…”
Get full text

A Method for Power Flow Estimation in Power Systems with Incomplete Data by He, Xuzhong, Yin, Yushan, Wang, Yuhong, Zheng, Zongsheng, Zhou, Xu

“…Machine learning-based power flow estimation is a critical technique for modeling the operational state of power systems. However, traditional power flow…”
Get full text

Unsupervised Convolutional Autoencoder-Based Feature Learning for Automatic Detection of Plant Diseases by Pardede, Hilman F., Suryawati, Endang, Sustika, Rika, Zilvan, Vicky

“…Developing an automatic detector of plant diseases is one of application fields in machine learning. Ground-truth diagnoses of plant diseases which are…”
Get full text

Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features by Liu, Bin, Li, Xiaofeng, Zheng, Gang

“…Researchers have already verified that the deep learning (DL) technology can realize accurate and robust mapping of tropical cyclone-induced coastal inundation…”
Get full text

Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper) by Alam, Mahabubul, Kundu, Satwik, Topaloglu, Rasit Onur, Ghosh, Swaroop

“…Image classification is a major application domain for conventional deep learning (DL). Quantum machine learning (QML) has the potential to revolutionize image…”
Get full text

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…”
Get full text

SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints by Li, Yahang, Wang, Zepeng, Lam, Fan

“…We present a novel method to enhance the SNR for multi-TE MR spectroscopic imaging (MRSI) data by integrating learned nonlinear low-dimensional model and…”
Get full text

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…”
Get full text

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…”
Get full text

KACNet: Kolmogorov-Arnold Convolution Network for Hyperspectral Anomaly Detection by Wu, Zhaoyue, Lu, Hailiang, Paoletti, Mercedes E., Su, Hongjun, Jing, Weipeng, Haut, Juan M.

“…Hyperspectral images capture numerous narrow spectral bands to provide detailed information to identify and locate targets, making them highly suitable for…”
Get full text

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…”
Get full text

Multiscale Spectral-Spatial Unmixing Network With Boltzmann-Inspired Adaptive Temperature by Wang, Zhixiang, Xu, Jindong, Wei, Guangyi, Wang, Jie, Yan, Yu

“…Hyperspectral unmixing aims to decompose mixed pixels into endmembers with corresponding abundances. However, while several existing convolutional autoencoder…”
Get full text

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…”
Get full text

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…”
Get full text

Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening by Alaverdyan, Zaruhi, Jung, Julien, Bouet, Romain, Lartizien, Carole

“…•We cast the challenging problem of detecting subtle brain lesions as a per voxel outlier detection problem.•Our brain anomaly detection model is trained on…”
Get full text

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…”
Get full text

A Deep Decomposition of MRI to Explore Neurodegeneration in Alzheimer's Disease by Martinez-Murcia, F. J., Gorriz, J. M., Ramirez, J., Castillo-Barnes, D., Segovia, F., Salas-Gonzalez, D., Ortiz, A.

“… Convolutional networks, and particularly convolutional autoen-coders are known for providing high-level abstract features that describe the internal distribution of data in high-dimensional manifolds…”
Get full text