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Initiating language engagement with multimodal learning tasks
Published 2024-09-01“…The present study explores the engagement among five engineering undergraduates for one semester while working on L2 tasks, which entailed the multimodal analysis of 8 technology-related TED Talks and was purposefully designed to initiate them into multimodal literacy and foster their language learning. …”
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Topological Data Analysis and Graph-Based Learning for Multimodal Recommendation
Published 2025-01-01Subjects: “…Multimodal recommendation systems…”
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Abnormality-aware multimodal learning for WSI classification
Published 2025-02-01“…To address these limitations, we propose the Abnormality-Aware MultiModal (AAMM) learning framework, which integrates abnormality detection and multimodal feature learning for WSI classification. …”
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A Comprehensive Review of Multimodal Analysis in Education
Published 2025-05-01“…Multimodal learning analytics (MMLA) has become a prominent approach for capturing the complexity of learning by integrating diverse data sources such as video, audio, physiological signals, and digital interactions. …”
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MMEmAsis: multimodal emotion and sentiment analysis
Published 2024-12-01Subjects: Get full text
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Exploring Studies on Multimodal Literacy in English Learning: A Bibliometric Analysis
Published 2024-11-01“…This study focuses on analyzing the productivity of research in multimodal literacy in English learning by using bibliometric analysis. …”
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Analysis of Multimodal Data in Project Management: Prospects for Using Machine Learning
Published 2024-02-01“…The results of the study allowed us to conclude that for the analysis of multimodal data, natural language processing and intellectual decision support technologies are most in demand, which can serve as the basis for new technological solutions in the field of project management.…”
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Multimodal Deep Learning for Android Malware Classification
Published 2025-02-01Subjects: “…multimodal deep learning for Android malware detection…”
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Dynamic Tuning and Multi-Task Learning-Based Model for Multimodal Sentiment Analysis
Published 2025-06-01Subjects: “…multimodal sentiment analysis…”
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Multimodal deep learning for art behavior analysis and personalized teaching path generation
Published 2025-08-01Subjects: “…Multimodal deep learning…”
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DSGRec: dual-path selection graph for multimodal recommendation
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Multimodal CustOmics: A unified and interpretable multi-task deep learning framework for multimodal integrative data analysis in oncology.
Published 2025-06-01“…The strength of our method lies in its capacity to unravel pathway activation through multimodal relationships and to extend enrichment analysis to spatial data for supervised tasks. …”
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Multimodal deep learning for cephalometric landmark detection and treatment prediction
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TMFN: a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis
Published 2025-01-01Subjects: “…Multimodal sentiment analysis…”
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Multimodal Analysis of Augmented Reality in Basic Programming Course: Innovation Learning in Modern Classes
Published 2024-12-01“…In this experimental study, a multimodal analysis and the ASSURE model were used in incorporating AR in a contemporary classroom. …”
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Multimodal learning for enhanced SPECT/CT imaging in sports injury diagnosis
Published 2025-07-01Subjects: Get full text
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Multimodal scene recognition using semantic segmentation and deep learning integration
Published 2025-05-01“…These results demonstrate how the multimodal approach can improve scene detection and classification, with potential uses in fields including robotics, sports analysis, and security systems.…”
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Multimodal Sentiment Analysis Based on Expert Mixing of Subtask Representations
Published 2025-01-01Subjects: “…Multimodal sentiment analysis…”
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Enhanced Rolling Bearing Fault Diagnosis Using Multimodal Deep Learning and Singular Spectrum Analysis
Published 2025-04-01“…A decision-level multimodal fusion deep learning strategy is proposed for the effective fault detection of rolling bearings based on long-term fault signals collected from multiple sensors. …”
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