Suchergebnisse - "Convolutional autoen-coder"

Deep Learning Approach for Epileptic Focus Localization von 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 …”
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A Method for Power Flow Estimation in Power Systems with Incomplete Data von 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 …”
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Unsupervised Convolutional Autoencoder-Based Feature Learning for Automatic Detection of Plant Diseases von 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 …”
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Automatic Mapping of Tropical Cyclone-Induced Coastal Inundation in SAR Imagery Based on Clustering of Deep Features von 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 …”
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Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper) von 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 …”
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Health indicator construction and status assessment of rotating machinery by spatio-temporal fusion of multi-domain mixed features von 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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SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints von 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 …”
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DFD-SS: Document Forgery Detection using Spectral – Spatial Features for Hyperspectral Images von 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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A Novel Hybrid Attentive Convolutional Autoencoder (HACA) Framework for Enhanced Epileptic Seizure Detection von 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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KACNet: Kolmogorov-Arnold Convolution Network for Hyperspectral Anomaly Detection von 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 …”
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Recurrent Nerual Imaging: An Evolutionary Approach for Mixed Possion-Gaussian Image Denoising von 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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Multiscale Spectral-Spatial Unmixing Network With Boltzmann-Inspired Adaptive Temperature von 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 …”
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Denoising Method for Wireless Communication Signals Based on Convolutional AutoEncoder von 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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Enhancing Image Security Using DNA and Deep Steganography von 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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Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening von 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 …”
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Generating Synthetic Short-Range FMCW Range-Doppler Maps Using Generative Adversarial Networks and Deep Convolutional Autoencoders von 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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A Deep Decomposition of MRI to Explore Neurodegeneration in Alzheimer's Disease von 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 …”
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