CentralNet: A Multilayer Approach for Multimodal Fusion

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

Gradient-based learning applied to document recognition

Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805

Distributed Representations of Words and Phrases and their Compositionality

Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533

Two-Stream Convolutional Networks for Action Recognition in Videos

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1406.2199 · Cited by 6,756

Multimodal Machine Learning: A Survey and Taxonomy

Baltrusaitis, T., Ahuja, C., & Morency, L.-P. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2798607 · Cited by 5,018

Deep Canonical Correlation Analysis

Andrew, G., Arora, R., Bilmes, J., & Livescu, K. (2013) · Cited by 1,603

ESC

Piczak, K. J. (2015) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2733373.2806390 · Cited by 1,572

YouTube-8M: A Large-Scale Video Classification BenchmarkPreprint

Abu-El-Haija, S., Kothari, N., Lee, J., Natsev, P., Toderici, G. D., Varadarajan, B., & Vijayanarasimhan, S. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.08675 · Cited by 1,382

Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects

Lahat, D., Adali, T., & Jutten, C. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2460697 · Cited by 1,296

Multimodal fusion for multimedia analysis: a survey

Atrey, P. K., Hossain, M. A., El Saddik, A., & Kankanhalli, M. S. (2010) · Multimedia Systems · doi:10.1007/s00530-010-0182-0 · Cited by 1,279

Generative Models vs Discriminative Models: Which Performs Better in Detecting Cyberbullying in Memes?

Jain, R., Maity, K., Jha, P., & Saha, S. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191363 · Cited by 4

Integration of audio-visual information for multi-speaker multimedia speaker recognition

Yang, J., Chen, F., Cheng, Y., & Lin, P. (2023) · Digital Signal Processing · doi:10.1016/j.dsp.2023.104315 · Cited by 5

Club Ideas and Exertions: Aggregating Local Predictions for Action Recognition

Cao, C., Li, J., Xi, R., & Zhang, Y. (2020) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2020.3017203 · Cited by 4

DeepMIN: Deep Multi-modal Interest Network with Cognitive Learning Modules

Zhang, Z., Li, Z., Jin, J., Gao, X., Yang, X., Zhang, B., & Xiao, L. (2025) · Lecture notes in computer science · doi:10.1007/978-981-97-5555-4_14 · Cited by 3

Task-Oriented Mulsemedia Communication Using Unified Perceiver and Conformal Prediction in 6G Wireless Systems

Guo, H., & Akyildiz, I. F. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3567880 · Cited by 4

Reconstruction-driven multimodal spectral feature fusion for diagnosis of benign and malignant thyroid tumors, lung cancer, aortic valve stenosis, and type A aortic dissection

Lin, J., Chang, C., Chen, C., Chen, C., & Lv, X. (2025) · Microchemical Journal · doi:10.1016/j.microc.2025.116619 · Cited by 3

AFE-YOLOv8: A Novel Object Detection Model for Unmanned Aerial Vehicle Scenes with Adaptive Feature Enhancement

Wang, S., Zhang, Z., Chao, Q., & Yu, T. (2024) · Algorithms · doi:10.3390/a17070276 · Cited by 4

Multimodal learning rebalanced: Negative correlation ensembles for improved performance

Wang, Z., Zhang, T., & Huang, W. X. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107686 · Cited by 3

GSS-RiskAsser: A Multi-Modal Deep-Learning Framework for Urban Gas Supply System Risk Assessment on Business Users

Li, X., Song, L., Liu, L., & Zhou, L. (2021) · Sensors · doi:10.3390/s21217010 · Cited by 3

M2-Mixer: A Multimodal Mixer with Multi-head Loss for Classification from Multimodal Data

Bezirganyan, G., Sellami, S., Berti‐Équille, L., & Fournier, S. (2023) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata59044.2023.10386252 · Cited by 3

Multimodal pre-train then transfer learning approach for speaker recognition

Jabeen, S., Amin, M. S., & Li, X. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18575-4 · Cited by 3

Quantifying the Impact of Complementary Visual and Textual Cues Under Image Captioning

Akilan, T., Thiagarajan, A., venkatesan, B., Thirumeni, S., & Chandrasekaran, S. G. (2020) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc42975.2020.9283183 · Cited by 3

Machine Learning Quorum Decider (MLQD) for Large Scale IoT Deployments

Ariharan, V., Eswaran, S. P., Vempati, S., & Anjum, N. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.04.134 · Cited by 3

Research on type-aware fashion compatibility prediction based on a hybrid attention mechanism

Li, Y., Li, G., Zhang, J., Jing, P., & Lu, X. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-023-18101-y · Cited by 2

Learning to Associate: Multimodal Inference with Fully Missing Modalities

Geraghty, J., Hines, A., & Golpayegani, F. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3746456 · Cited by 2

MMFC-PFL: Multimodal Feature Collaborative Personalized Federated Learning

Li, D., Weng, Z., Yao, J., Xuan, Z., & Wang, Z. (2026) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2026.3656183 · Cited by 2

Multimodal Graph Representation Learning over Arbitrary Sets of Modalities

Patapati, S., & Srinivasan, T. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00686 · Cited by 2

Post-hurricane building damage assessment using street-view imagery and structured data: a multimodal deep learning approach

Zhang, X., Xue, Z., Prevatt, D. O., Bridge, J. A., Xu, S., & Zhao, X. (2026) · Urban Lifeline · doi:10.1007/s44285-026-00070-x · Cited by 2

Determining Wave Height from Nearshore Videos Based on Multi-level Spatiotemporal Feature Fusion

Song, W. G., Li, Q., He, Q., Zhou, X., & Chen, Y. (2021) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn52387.2021.9534048 · Cited by 2

Star-Net: a Multi-Branch Convolutional Network for Multiple Source Image Segmentation

Placidi, G., Cinque, L., Nappi, M., Polsinelli, M., Sciarra, A., & Tortora, G. (2022) · International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) · doi:10.1109/sitis57111.2022.00034 · Cited by 2

TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data

Myers, A., Kvinge, H., & Emerson, T. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00067 · Cited by 2

Attention synergy adaptive fusion convolutional neural network for multilabel skin lesion classification

Li, R., Jiang, C., & Chen, N. (2025) · International Conference on Computer Vision and Image Processing (CVIP) · doi:10.1117/12.3057963 · Cited by 2

U‐shaped network combining dual‐stream fusion mamba and redesigned multilayer perceptron for myocardial pathology segmentation

Zhang, W., Yang, T., Fan, J., Wang, H., Ji, M., Zhang, H., & Miao, J. (2025) · Medical Physics · doi:10.1002/mp.17812 · Cited by 2

Data and Decision Fusion with Uncertainty Quantification for ML-based Healthcare Decision Systems

Bezirganyan, G. (2023) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3583780.3616004 · Cited by 2

The Effect CoronaVirus Pendamic on Education into Electronic Multi-modal Smart Education

El-Din, D. M., Hassanein, A. E., & Hassanien, E. E. (2020) · Studies in big data · doi:10.1007/978-3-030-55258-9_15 · Cited by 2

Image-Label Recovery on Fashion Data Using Image Similarity from Triple Siamese Network

Banerjee, D., Kyrarini, M., & Kim, W. H. (2021) · Technologies · doi:10.3390/technologies9010010 · Cited by 2

G 2 D: Boosting Multimodal Learning with Gradient-Guided Distillation

Rakib, M., & Bagavathi, A. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00387 · Cited by 1

Multi-Branch Tree-Based Fusion Neural Architecture Search With Zero-Cost Screen for Multi-Modal Classification

Guo, Q. J., Su, Q., Liang, X., Qian, Y., Li, N., & Cui, Z. (2026) · IEEE Transactions on Image Processing · doi:10.1109/tip.2026.3706305 · Cited by 2

ML-TFN: Multi Layers Tensor Fusion Network for Affective Video Content Analysis

Wang, Q., Xiang, X., & Zhao, J. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-6142-7_14 · Cited by 1

Efficient Spatio-Temporal Randomly Wired Neural Networks for Traffic Forecasting

Li, S., Bao, K., Ke, S., Li, C., Zhang, J., & Zheng, Y. (2022) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw58026.2022.00140 · Cited by 1

Image Fusion Survey: A Novel Taxonomy Integrating Transformer and Recent Approaches

Gwendal, B., Strubel, D., Brisebarre, G., Jean-François, G., Ardabilian, M., & Dellandréa, E. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-88217-3_12 · Cited by 1

Enhancing Thai Food Recognition Through Multimodal Fusion of Image and Fourier Spectrum

Pasupa, K., & Woraratpanya, K. (2024) · Communications in computer and information science · doi:10.1007/978-981-97-5934-7_7 · Cited by 1

Multi-Level Sensor Fusion with Deep Learning

Vielzeuf, V., Lechervy, A., Pateux, S., & Jurie, F. (2018) · HAL · doi:10.48550/arxiv.1811.02447 · Cited by 1

Image Captioning with Complementary Visual and Textual CuesPreprint

venkatesan, B., & Sond, R. K. (2020) · doi:10.36227/techrxiv.12093564.v1 · Cited by 1

Auto-weighting for Breast Cancer Classification in Multimodal UltrasoundPreprint

Jian, W., Miao, J., Xin, Y., Li, R., Guangquan, Z., Yuhao, H., Lin, Z., Xue, W., Xiaohong, J., Zhou, J., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.03435 · Cited by 1

Deep audio and video emotion detection

Aminbeidokhti, M. (2020) · Espace ÉTS (ETS)

Looking Farther in Parametric Scene Parsing with Ground and Aerial Imagery

Modhugu, R., Sethuram, H. R., Chandraker, M. K., & Jawahar, C. V. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9561825

Image Captioning with Complementary Visual and Textual CuesPreprint

venkatesan, B., & Sond, R. K. (2020) · doi:10.36227/techrxiv.12093564

MM-GATBT: Enriching Multimodal Representation Using Graph Attention Network

Seo, S. B., Nam, H., & Delgosha, P. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop (NAACL SRW) · doi:10.18653/v1/2022.naacl-srw.14

MVSF: Multi-View Signature Fusion Network for Noninvasively Predicting Ki67 Status

Li, X., Cheng, J., Liu, J., Kuang, H., Shen, C., Yang, P., & Wang, J. (2022) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm55620.2022.9995030

Granularity Based Inter and Intra-Modal Fusion Network for Sarcasm DetectionPreprint

Shi, Y., Zhao, X., & Chen, M. (2023) · Research Square · doi:10.21203/rs.3.rs-3476391/v1

Inputmix: A Strategy to Regularize and Balance Multi-Modality and Multi-View Model Learning

Wang, J., & Nordström, T. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446664

SSDC-Net: An Effective Classification Method of Steel Surface Defects Based on Salient Local Features

Hao, Q., Gan, Q., Liu, Z., Chen, J., Shen, Q., Qian, C., & Liu, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5588-2_41

Energy-Induced Explicit Quantification for Multi-modality MRI Fusion

Qi, X., Zhang, Y., Wang, T., Yang, G., Jin, Y., & Li, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72667-5_25

Intensity Controllable Emotional Speech Synthesis Based on Valence-Arousal-Dominance

Li, G., & Chen, Y. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-2882-7_4

Multi‐view sparse attention network for glioma survival risk prediction

Li, X., Kuang, H., Cheng, J., Luo, Y. P., He, M., & Wang, J. (2025) · Medical Physics · doi:10.1002/mp.17774

Core structure-guided multi-modal classification via Monte Carlo Tree Search

Liu, G., Qian, Y., Liang, X., & Fu, P. (2025) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-025-02606-z

Topologically Consistent Prototype Network for Incomplete Multimodal Learning

Wang, Y., Zhang, X.-Y., & Liu, C. (2025) · Cognitive Computation · doi:10.1007/s12559-025-10448-8

An Enhanced Feature Fusion Network for Multimodal Sentiment Analysis

Xu, Y. L., & Wu, Y. (2024) · Asian Conference on Artificial Intelligence Technology (ACAIT) · doi:10.1109/acait63902.2024.11022222

Highlight Detection in Podcasts: A Multimodal Deep Learning Approach

Phuengpanyaloet, W., Boonruengkhao, N., Anchutin, V., Pasupa, K., & Loo, C. K. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-6599-0_15

ExGAT: Build Explicit Dependencies for Incomplete Multi-Modal Learning via Graph Attention Network

Zhao, B., Zhāng, W., & Zou, Z. (2025) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme59968.2025.11209190

EPIC: Efficient Prompt Interaction for Text-Image Classification

Yu, X., Sun, H., Ling, Z., Niu, Z., Bai, Z., Qin, R., Chen, Y.-W., & Lin, L. (2025) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme59968.2025.11210028

DTCFormer: Deep tensor chain frequency guided transformer for multi-modal medical image classification

Wang, Z., Di, H., Zhang, R., & Liu, F. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.109152 · Cited by 1

Dual Selective Attention Model for Sentiment and Emotion Identification with Explainable Cause Generation

Deria, A., Dey, S., & Ganguly, D. (2026) · Lecture notes in networks and systems · doi:10.1007/978-981-96-8309-3_13

Self-Balancing Multimodal Models via Multi-Loss Gradient Modulation

Kontras, K., Chatzichristos, C., Blaschko, M. B., & Vos, M. D. (2026) · International Journal of Computer Vision · doi:10.1007/s11263-025-02696-w · Cited by 21

Granularity-guided fusion for multi-modal sentiment understanding

Chen, M., Tang, H., Sun, C., & Zhang, N. (2026) · Scientific Reports · doi:10.1038/s41598-026-43363-5

Apprentissage neuronal profond pour l'analyse de contenus multimodaux et temporels

Vielzeuf, V. (2019) · theses.fr (ABES) · doi:10.70675/cd4ec871zb372z492fz94bfz25086c5fda4a

Real-time multimodal semantic scene understanding for autonomous UGV navigation

Zhang, Y. (2021) · theses.fr (ABES) · doi:10.70675/a471d7bez2ff1z44feza0b4z4beabc22b5ab

Visual and Textual Common Semantic Spaces for the Analysis of Multimodal Content

Beltrán, L. V. B. (2021) · theses.fr (ABES) · doi:10.70675/a19cbe0dz6c94z4ff6zb70ez024fd8546d17

Correlation Aware Imbalanced Multimodal Fusion in IoT Environment

Zhang, W., Huang, Y., Li, Q., Shi, N., & Xiong, W. (2026) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-032-21171-2_7

Lightweight surprise-on-memory: efficient engagement recognition via prediction error-guided updates

Zhang, X., Sun, Y., & Ji, W. (2026) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-026-00801-8

Generalizable and Robust Beam Prediction for 6G Networks: An Deep-Learning Framework With Positioning Feature Fusion

Jin, Y., Li, Y., Jiang, J., Gao, Y., Liu, S., Du, J., Yang, Z., & Xu, S. (2026) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2026.3695479

CaLB: Caption and Language-Based with Simple Fusion Network

Shi, Y., Wu, S., Ding, Z., Shao, H., & Li, Y. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-6817-8_40

Multimodal fault diagnosis method of bogie motor based on physics-inspired regularization and enhanced ConvNeXt

Yang, P., Huang, Y., & Chen, J. (2026) · Scientific Reports · doi:10.1038/s41598-026-61669-2

RE-MMNAS: LLM Reasoning-Guided Evolutionary Architecture Search for Multi-Modal Feature Fusion

Xiao, H., Yan, X., Xie, Y. H., & Huang, H. P. (2026) · Genetic and Evolutionary Computation Conference Companion (GECCO Companion) · doi:10.1145/3795101.3814657

Ker-S6DSF: Selective State-Space-Based Dual-Stream Fusion for Keratoconus Screening

Sazak, H., Kotan, M., & Çakır, B. K. (2026) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-026-11688-y

Align-then-Aggregate: Pretreatment prediction of radiation-induced lymphopenia in nasopharyngeal carcinoma via multi-modal collaborative learning

Zhao, R., Deng, H., Wu, Z., & Zhang, Z. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.111496

Early vs Late Fusion in Multimodal Convolutional Neural Networks

Gadzicki, K., Khamsehashari, R., & Zetzsche, C. (2020) · International Conference on Information Fusion (FUSION) · doi:10.23919/fusion45008.2020.9190246 · Cited by 299

Learn to combine modalities in multimodal deep learning

Liu, K., Li, Y., Xu, N., & Natarajan, P. (2018) · arXiv · doi:10.48550/arxiv.1805.11730 · Cited by 136

Learning Joint Multimodal Representation Based on Multi-fusion Deep Neural Networks

Gu, Z., Lang, B., Yue, T., & Huang, L. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-70096-0_29 · Cited by 19

Method of graph fusion of multimodal data using multitask learning

Merkotan, D., & Trotsko, O. (2025) · Communication informatization and cybersecurity systems and technologies · doi:10.58254/viti.8.2025.11.133

Robust Deep Multi-modal Learning Based on Gated Information Fusion Network

Kim, J., Koh, J., Kim, Y., Choi, J., Hwang, Y., & Choi, J. W. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-20870-7_6 · Cited by 82