Search Results - "Deep Autoencoder"

A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework by Sampaio, Inês Won, Tassi, Emma, Bellani, Marcella, Benedetti, Francesco, Nenadić, Igor, Phillips, Mary L., Piras, Fabrizio, Yatham, Lakshmi, Bianchi, Anna Maria, Brambilla, Paolo, Maggioni, Eleonora

“…). We used deep autoencoders in an anomaly detection framework, combined for the first time with a confounder removal step that integrates training and external validation…”
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Anomaly detection in surveillance videos using deep autoencoder by Mishra, Sarthak, Jabin, Suraiya

“… In this work, we present a novel anomaly detection algorithm using deep autoencoders which exploits spatiotemporal features of training video clips along with a novel combined regularity score-based…”
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Man-Recon: Manifold Learning For Reconstruction With Deep Autoencoder For Smart Seismic Interpretation by Mustafa, Ahmad, AlRegib, Ghassan

“… For many tasks however, annotating data has significant costs in terms of time and money, owing to the high standards of subject matter expertise required, for example in medical and geophysical…”
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Sample reconstruction with deep autoencoder for one sample per person face recognition by Zhang, Yan, Peng, Hua

“… variations of multi-sample subjects to single-sample subjects by deep autoencoder and reconstruct new samples…”
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CDDA: color-dominant deep autoencoder for faster and efficient bilateral image filtering by Das, Apurba, Shylaja, S. S.

“… The solution speeds up the filtering algorithm further by psycho-visual saliency-based deep encoded dominant color gamut, learned for different subject classes of images…”
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Multimodal and multicontrast image fusion via deep generative models by Dimitri, Giovanna Maria, Spasov, Simeon, Duggento, Andrea, Passamonti, Luca, Lió, Pietro, Toschi, Nicola

“…•Deep learning architecture for neuroimaging reconstruction.•Efficient convolutional neural networks based on separable convolutions.•Multimodality learning…”
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Enhanced Anomaly Detection in IoT Networks Using Deep Autoencoders with Feature Selection Techniques by Rhachi, Hamza, Balboul, Younes, Bouayad, Anas

“… Still, these networks are subject to various types of attacks that will lead to the loss of user data…”
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Dynamic Viewing Pattern Analysis: Towards Large-Scale Screening of Children With ASD in Remote Areas by Xia, Chen, Zhang, Dingwen, Li, Kuan, Li, Hongxia, Chen, Jianxin, Min, Weidong, Han, Junwei

“…Objective : Autism spectrum disorder (ASD) affects nearly 1 in 44 children younger than 8 years old in the United States, and the situation may be even worse…”
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Visual image reconstructed without semantics from human brain activity using linear image decoders and nonlinear noise suppression by Li, Qiang

“…In recent years, substantial strides have been made in the field of visual image reconstruction, particularly in its capacity to generate high-quality visual…”
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A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework by Sampaio, Inês Won, Tassi, Emma, Bellani, Marcella, Benedetti, Francesco, Nenadic, Igor, Phillips, Mary, Piras, Fabrizio, Yatham, Lakshmi, Bianchi, Anna Maria, Brambilla, Paolo, Maggioni, Eleonora

“…). We employed deep autoencoders in an anomaly detection framework, combined with a confounder removal step integrating training and external validation…”
Get full text

Man-recon: manifold learning for reconstruction with deep autoencoder for smart seismic interpretation by Ahmad, Mustafa, AlRegib, Ghassan

“… For many tasks however, annotating data has significant costs in terms of time and money, owing to the high standards of subject matter expertise required, for example in medical and geophysical…”
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A Deep Learning-Based Compression Algorithm for 9-DOF Inertial Measurement Unit Signals Along With an Error Compensating Mechanism by Sepahvand, Majid, Abdali-Mohammadi, Fardin

“…Inertial sensors with microelectromechanical systems technology are an integral part of many modern electronic devices such as wearable medical products, which are inherently subject to memory…”
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Improving Motor Imagery EEG Signal Classification Using Deep Learning Techniques by Velakanti, Gouthami, Mahveen, Safa, Rao, A. Abhinav, Sai Hanith, M., Priya, G. Krishna, Sushrith Reddy, K.

“…), a Deep Autoencoder (DAE), and a hybrid Convolutional Neural Network-Long Short Term Memory (CNN-LSTM…”
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Anomaly-Based Insider Threat Detection Using Deep Autoencoders by Liu, Liu, De Vel, Olivier, Chen, Chao, Zhang, Jun, Xiang, Yang

“…In recent years, the malicious insider threat has become one of the most significant cyber security threats that an organisation can be subject…”
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Mapping individual differences in cortical architecture using multi-view representation learning by Sellami, Akrem, Dupe, Francois-Xavier, Cagna, Bastien, Kadri, Hachem, Ayache, Stephane, Artieres, Thierry, Takerkart, Sylvain

“…) has proven invaluable. For this, neuroscientists rely on basic methods such as univariate linear correlations between single brain features and a score that quantifies either the severity of a disease or the subject's…”
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Hippocampus Segmentation Based on Iterative Local Linear Mapping With Representative and Local Structure-Preserved Feature Embedding by Pang, Shumao, Feng, Qianjin, Lu, Zhentai, Jiang, Jun, Zhao, Lei, Lin, Liyan, Li, Xueli, Lian, Tao, Huang, Meiyan, Yang, Wei

“… In the proposed approach, semi-supervised deep autoencoder (SSDA) exploits unsupervised deep autoencoder…”
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Personalized MRI-based characterization of subcortical anomalies in Ataxia-Telangiectasia using deep-learning by Saini, Catalina, Salazar-Vilches, Cristian, Blanchard, Caroline C.V., Whitehouse, William P., Parra, Denis, Dineen, Rob A., Pszczolkowski, Stefan

“… A normative deep autoencoder that reconstructs these features was trained on healthy subjects…”
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Deep-Cascade: Cascading 3D Deep Neural Networks for Fast Anomaly Detection and Localization in Crowded Scenes by Sabokrou, Mohammad, Fayyaz, Mohsen, Fathy, Mahmood, Klette, Reinhard

“… Time-efficient anomaly localization is an ongoing challenge and subject of this paper…”
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Enhancing biomechanical machine learning with limited data: generating realistic synthetic posture data using generative artificial intelligence by Dindorf, Carlo, Dully, Jonas, Konradi, Jürgen, Wolf, Claudia, Becker, Stephan, Simon, Steven, Huthwelker, Janine, Werthmann, Frederike, Kniepert, Johanna, Drees, Philipp, Betz, Ulrich, Fröhlich, Michael

“…) to produce realistic synthetic posture data by utilizing three-dimensional posture data. Methods: Data were collected from 338 subjects through surface topography…”
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Multimodal Emotion Recognition in Response to Oil Paintings by Luo, Shuai, Lan, Yu-Ting, Peng, Dan, Li, Ziyi, Zheng, Wei-Long, Lu, Bao-Liang

“…) exploring topological information embedded in EEG channels with graph neural networks (GNNs), and 3) combining EEG and eye tracking data with a deep autoencoder…”
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