Search Results - Multi-modal autoencoder

Multi-modal graph convolutional network for vessel trajectory prediction based on cooperative intention enhance using conditional variational autoencoder

Authors: Jiang, Junhao Zuo, Yi Li, Zhiyuan

Source: Reliability Engineering and System Safety. 267

Subject Terms: Graph convolutional network, Trajectory prediction, Cooperative intention constructor, Intelligent situational awareness systems, Conditional variational autoencoder, Multi-modal interaction extractor

Access URL: https://research.chalmers.se/publication/549377

Multimae Meets Earth Observation: Pre-Training Multi-Modal Multi-Task Masked Autoencoders for Earth Observation Tasks

Authors: Sosa, Jose Rukhovich, Danila Kacem, Anis et al.

Source: 2025 IEEE International Conference on Image Processing (ICIP). :797-802

Subject Terms: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/2505.14951

Robust anomaly detection through multi-modal autoencoder fusion for small vehicle damage detection

Authors: Sara Khan Mehmed Yüksel Frank Kirchner

Source: Machine Learning with Applications, Vol 22, Iss , Pp 100794- (2025)

Subject Terms: Multi-modal, Autoencoders, Sensors, Automotive, Signal processing, Deep learning, Cybernetics, Q300-390, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S266682702500177X; https://doaj.org/toc/2666-8270

Access URL: https://doaj.org/article/967adec2abd14f09aaf640bb3175d464

Multi-Modal Contrastive Masked Autoencoders: A Two-Stage Progressive Pre-training Approach for RGBD Datasets

Authors: Muhammad Abdullah Jamal Omid Mohareri

Source: 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). :17947-17957

Automated Anomaly Detection and Risk Stratification in Polymerization Reactor Systems via Multi-Modal Data Fusion and Conditional Variational Autoencoders

Authors: Freederia AI Researcher

Learning novel representations of variable sources from multi-modal data via autoencoders

Authors: P. Huijse J. De Ridder L. Eyer et al.

Source: Astronomy & Astrophysics.

MyeVAE: a multi-modal variational autoencoder for risk profiling of newly diagnosed multiple myeloma

Authors: Jia Geng Chang Jianbin Chen Guo-Liang Chew et al.

Source: BMC Artificial Intelligence. 1

Low-rank Multi-modal Features Fusion Semantic Autoencoder For Zero-shot Learning

Authors: Miao Luo Xing Chu Haiyang Zhao

Source: 2024 International Conference on Virtual Reality and Visualization (ICVRV). :13-18

AutoEncoder-based Weighted Multi-modal Knowledge Graph Representation Learning

Authors: Xiaolong Qu Dongmei Li Haipeng Zhang et al.

Source: Proceedings of the 2024 10th International Conference on Communication and Information Processing. :652-659

Multi-Modal Intermediate Feature Interaction Autoencoder for Overall Survival Prediction of Esophageal Squamous Cell Cancer

Authors: Wu, Chengyu Zhang, Yatao Wang, Yaqi et al.

Source: 2024 IEEE International Symposium on Biomedical Imaging (ISBI). :1-5

Subject Terms: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, 3. Good health

Access URL: http://arxiv.org/abs/2408.13290

Improving Normative Modeling for Multi-Modal Neuroimaging Data Using Mixture-of-Product-of-Experts Variational Autoencoders

Authors: Kumar, Sayantan Payne, Philip Sotiras, Aristeidis

Source: 2024 IEEE International Symposium on Biomedical Imaging (ISBI). :1-5

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Machine Learning (cs.LG)

Access URL: https://pubmed.ncbi.nlm.nih.gov/39610661
http://arxiv.org/abs/2312.00992

MoCA: Multi-modal Cross-masked Autoencoder for Digital Health Measurements

Authors: Ryu, Howon Chen, Yuliang Wang, Yacun et al.

Subject Terms: Machine Learning, FOS: Computer and information sciences, Applications, Machine Learning (stat.ML), Applications (stat.AP), Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2506.02260

FreqMAE: Frequency-Aware Masked Autoencoder for Multi-Modal IoT Sensing

Authors: Denizhan Kara Tomoyoshi Kimura Shengzhong Liu et al.

Source: Proceedings of the ACM Web Conference 2024. :2795-2806

TransMCS: A hybrid CNN-transformer autoencoder for end-to-end multi-modal medical signals compressive sensing

Authors: Yinghao Zhang Xuanzhe Xiao Jianxiong Guo

Source: Theoretical Computer Science. 1051:115409

MultiMAE for Brain MRIs: Robustness to Missing Inputs Using Multi-Modal Masked Autoencoder

Authors: Erdur, Ayhan Can Beischl, Christian Scholz, Daniel et al.

Subject Terms: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/2509.11442

Robust Anomaly Detection through Multi-Modal Autoencoder Fusion for Small Vehicle Damage Detection

Authors: Khan, Sara Yüksel, Mehmed Kirchner, Frank

Subject Terms: Machine Learning, FOS: Computer and information sciences, Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2509.01719

M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation

Authors: He, Chuan Liu, Yongchao Li, Qiang et al.

Subject Terms: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Information Retrieval, Information Retrieval (cs.IR)

Access URL: http://arxiv.org/abs/2508.00452

M33D: Learning 3D priors using Multi-Modal Masked Autoencoders for 2D image and video understanding

Authors: Jamal, Muhammad Abdullah Mohareri, Omid

Source: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). :2532-2542

Subject Terms: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/2309.15313

SC-PCA-Enr: multi-modal residual adaption enabled Shearlet-Contourlet autoencoder for fused multi-modal image enhancement

Authors: Nitin Sudhakarrao Thakare Mukesh Yadav

Source: International Journal of Signal and Imaging Systems Engineering. 13:203-217

Personalized design aesthetic preference modeling: a variational autoencoder and meta-learning approach for multi-modal feature representation and transfer optimization.

Authors: Chen C Gong Z

Source: Scientific reports [Sci Rep] 2025 Nov 24; Vol. 15 (1), pp. 41727. Date of Electronic Publication: 2025 Nov 24.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE