Search Results - "Multi-modal autoencoder"

Thermal-visible stereo matching at night based on Multi-Modal Autoencoder by Zhang, Quan, Li, Yiran, Yang, Le, Zhang, Yi, Li, Zechao, Chen, Xiaoyu, Han, Jing

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Robust anomaly detection through multi-modal autoencoder fusion for small vehicle damage detection by Khan, Sara, Yüksel, Mehmed, Kirchner, Frank

“…Wear and tear detection in fleet and shared vehicle systems is a critical challenge, particularly in rental and car-sharing services, where minor damage, such…”
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Prediction of Drug-Target Interactions Based on Multi-Modal Autoencoder by Wang, Cheng, Zhao, Zonghao, Gu, Pandeng, Chen, Chong, Hu, Yuxia, Xu, Heng, Sun, Long, Shao, Hui

“… In this work, the multi-modal autoencoder is used to fuse the similarity networks of many different drugs (targets…”
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A graph-based semi-supervised approach to classification learning in digital geographies by Liu, Pengyuan, De Sabbata, Stefano

“…As the distinction between online and physical spaces rapidly degrades, social media have now become an integral component of how many people's everyday…”
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Prediction of Recurrence Probability of Thyroid Cancer Patients using Similarity Loss based Multi-modal Autoencoder by Kim, Jaehyun, Shin, Hyunjung

“…Data used for the diagnosis of thyroid cancer patients include Thyroid Stimulating hormone (TSH), Thyroglobulin (Tg), Tg Antibodies (TgAb), and pathology…”
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DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer’s Disease by Chyr, Jacqueline, Gong, Haoran, Zhou, Xiaobo

“…: (1) a multi-modal autoencoder to integrate heterogeneous drug information and (2) a Wasserstein variational autoencoder…”
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Representation learning using step-based deep multi-modal autoencoders by Bhatt, Gaurav, Jha, Piyush, Raman, Balasubramanian

“…Deep learning techniques have been successfully used in learning a common representation for multi-view data, wherein different modalities are projected onto a…”
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Predicting Drug Classification Codes by Feature Integration Using Multi-modal Autoencoders by Jung, Yi-Sue, Park, Jong-Hoon, Cho, Young-Rae

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Multimodal Imputation-Based Multimodal Autoencoder Framework for AQI Classification and Prediction of Indian Cities by Srinivasa Rao, Routhu, Rao Kalabarige, Lakshmana, Holla, M. Raviraja, Kumar Sahu, Aditya

“…) with the features of multi-modal autoencoder (MMA) and fed to an XGBoost(XGB) algorithm for AQI prediction and classification…”
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Multi-Modal Cross Learning for an FMCW Radar Assisted by Thermal and RGB Cameras to Monitor Gestures and Cooking Processes by Altmann, Marco, Ott, Peter, Stache, Nicolaj C., Waldschmidt, Christian

“…). The proposed approach uses a multi-modal autoencoder training which creates a compressed data representation containing correlated features across modalities…”
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Multi-Modal Stacked Denoising Autoencoder for Handling Missing Data in Healthcare Big Data by Kim, Joo-Chang, Chung, Kyungyong

“… In this study, a method for estimating missing data using a multi-modal autoencoder applied to the field of healthcare big data is proposed…”
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PTFNet: Robotic-Relevant, Single-View Obstacle Footprint Estimation From Sparse and Incomplete Point Clouds by Cop, Konrad P., Trzcinski, Tomasz P.

“…In order for robots to navigate successfully, they need to correctly estimate the traversability of their surroundings. To do so, an orthogonal projection of…”
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Multi-source attention autoencoder network for hyperspectral unmixing with LiDAR data by Hu, Jiwei, Bai, Yangrui, Li, Zijun, Jin, Qiwen, Peng, Chengli

“…Autoencoder (AE) based on Convolutional Neural Networks (CNN) has demonstrated excellent capabilities in capturing high-dimensional features, finding…”
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Evaluation of Source-wise Missing Data Techniques for the Prediction of Parkinson's Disease Using Smartphones by Prince, John, Andreotti, Fernando, De Vos, Maarten

“… source-wise missing data is simulated. The classification accuracy and imputation error of five missing data techniques, including a multi-modal autoencoder and multi-source ensemble learning, are compared at varying levels of missingness…”
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Multi-modal Asymmetric Autoencoders for Massive Photo Collection Applications by Hamrouni, Aymen, Ghazzai, Hakim, Massoud, Yehia

“…There has been an abundant use of applications where many photos obtained from camera-equipped devices can be leveraged and exploited to enable emerging…”
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DenoMAE: A Multimodal Autoencoder for Denoising Modulation Signals by Faysal, Atik, Boushine, Taha, Rostami, Mohammad, Roshan, Reihaneh Gh, Wang, Huaxia, Muralidhar, Nikhil, Sahoo, Avimanyu, Yao, Yu-Dong

“…We propose Denoising Masked Autoencoder (DenoMAE), a novel multimodal autoencoder framework for denoising modulation signals during pretraining…”
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Deep multimodal autoencoder for crack criticality assessment by Launay, Hugo, Ryckelynck, David, Lacourt, Laurent, Besson, Jacques, Mondon, Arnaud, Willot, Francois

“… A multimodal autoencoder enables to mix morphological and mechanical data. It contains a single…”
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Joint ECG–EMG–EEG signal compression and reconstruction with incremental multimodal autoencoder approach by Dasan, Evangelin, Gnanaraj, Rajakumar

“…Through wearable technology, several chronic diseases are diagnosed by long-term monitoring of vital signs specifically ECG, EMG, EEG biosignals. Such…”
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MOADE: a multimodal autoencoder for dissociating bulk multi-omics data by Sun, Jiao, Malik, Ayesha A., Lin, Tong, Bratton, Ayla, Pan, Yue, Smith, Kyle, Onar-Thomas, Arzu, Robinson, Giles W., Zhang, Wei, Northcott, Paul A., Li, Qian

“… Here, we present MOADE, a multimodal autoencoder pipeline linking multi-dimensional features to jointly predict personalized multi-omic profiles and cellular compositions, using pseudo-bulk data…”
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Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals by Sirpal, Parikshat, Damseh, Rafat, Peng, Ke, Nguyen, Dang Khoa, Lesage, Frédéric

“…In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy…”
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