CentralNet: A Multilayer Approach for Multimodal Fusion

Very Deep Convolutional Networks for Large-Scale Image Recognition

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Gradient-based learning applied to document recognition

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Distributed Representations of Words and Phrases and their Compositionality

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Two-Stream Convolutional Networks for Action Recognition in Videos

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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

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ESC

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

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

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Multimodal fusion for multimedia analysis: a survey

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Multimodal intelligence: Representation learning, information fusion, and applications

Zhang, C., Yang, Z., He, X., & Deng, L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.2987728 · Cited by 511

MMTM: Multimodal Transfer Module for CNN Fusion

Joze, H. R. V., Shaban, A., Iuzzolino, M. L., & Koishida, K. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01330 · Cited by 337

SMIL: Multimodal Learning with Severely Missing Modality

Ma, M., Ren, J., Zhao, L., Tulyakov, S., Wu, C., & Peng, X. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i3.16330 · Cited by 332

Multi-Modal Learning with Missing Modality via Shared-Specific Feature Modelling

Wang, H., Chen, Y., Ma, C., Avery, J., Hull, M. L., & Carneiro, G. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01524 · Cited by 262

Multimodal Co-learning: Challenges, applications with datasets, recent advances and future directions

Rahate, A., Walambe, R., Ramanna, S., & Kotecha, K. (2022) · Information Fusion · doi:10.1016/j.inffus.2021.12.003 · Cited by 214

MFAS: Multimodal Fusion Architecture Search

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Multimodal Deep Learning

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Are Multimodal Transformers Robust to Missing Modality?

Ma, M., Ren, J., Zhao, L., Testuggine, D., & Peng, X. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01764 · Cited by 198

Supervised Multimodal Bitransformers for Classifying Images and TextPreprint

Kiela, D., Bhooshan, S., Firooz, H., Perez, E., & Testuggine, D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.02950 · Cited by 345

PMR: Prototypical Modal Rebalance for Multimodal Learning

Fan, Y., Xu, W., Wang, H., Wang, J., & Guo, S. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01918 · Cited by 185

Dynamic Multimodal Fusion

Xue, Z., & Marculescu, R. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00256 · Cited by 161

Co-Attention Fusion Network for Multimodal Skin Cancer Diagnosis

He, X., Wang, Y., Zhao, S., & Chen, X. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108990 · Cited by 97

Adaptive Multimodal Emotion Detection Architecture for Social Robots

Heredia, J., Lopes-Silva, E., Cardinale, Y., Díaz-Amado, J., Dongo, I., Graterol, W., & Aguilera, A. (2022) · IEEE Access · doi:10.1109/access.2022.3149214 · Cited by 99

A Multimodality Fusion Deep Neural Network and Safety Test Strategy for Intelligent Vehicles

Nie, J., Yan, J., Yin, H., Ren, L., & Meng, Q. (2020) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2020.3027319 · Cited by 94

Multi-Modal Machine Learning in Engineering Design: A Review and Future Directions

Song, B., Zhou, R., & Ahmed, F. (2023) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4063954 · Cited by 105

Optical and Synthetic Aperture Radar Image Fusion for Ship Detection and Recognition: Current state, challenges, and future prospects

Zhang, Z., Zhang, L., Wu, J., & Guo, W. (2024) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2024.3404506 · Cited by 91

AWSnet: An auto-weighted supervision attention network for myocardial scar and edema segmentation in multi-sequence cardiac magnetic resonance images

Wang, K., Yang, X., Miao, J., Li, L., Yao, J., Zhou, P., Xue, W., Zhou, G., Zhuang, X., & Ni, D. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102362 · Cited by 68

Boosting Multi-modal Model Performance with Adaptive Gradient Modulation

Li, H., Li, X., Hu, P., Lei, Y., Li, C., & Zhou, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.02030 · Cited by 64

A Simple Visual-Textual Baseline for Pedestrian Attribute Recognition

Cheng, X., Jia, M., Wang, Q., & Zhang, J. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3178144 · Cited by 61

TMMF: Temporal Multi-Modal Fusion for Single-Stage Continuous Gesture Recognition

Gammulle, H., Denman, S., Sridharan, S., & Fookes, C. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3108349 · Cited by 50

Expanding Large Pre-trained Unimodal Models with Multimodal Information Injection for Image-Text Multimodal Classification

Liang, T., Lin, G., Wan, M., Li, T., Ma, G., & Lv, F. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01505 · Cited by 44

Enhancing Multimodal Cooperation via Sample-Level Modality Valuation

Wei, Y., Feng, R., Wang, Z., & Hu, D. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.02581 · Cited by 45

MSAF: Multimodal Split Attention FusionPreprint

Su, L., Hu, C., Li, G., & Cao, D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.07175 · Cited by 72

Multimodal Attention Network for Continuous-Time Emotion Recognition Using Video and EEG Signals

Choi, D. Y., Kim, D.-H., & Song, B. C. (2020) · IEEE Access · doi:10.1109/access.2020.3036877 · Cited by 39

Dense Modality Interaction Network for Audio-Visual Event Localization

Liu, S., Quan, W., Wang, C., Liu, Y., Liu, B., & Dong-ming Yan, A. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3150469 · Cited by 37

Multimodal analysis of personality traits on videos of self-presentation and induced behavior

Giritlioğlu, D., Mandira, B., Yilmaz, S. F., Ertenli, C. U., Akgür, B. F., Kınıklıoğlu, M., Kurt, A. G., Mutlu, E., Gürel, Ş. C., & Dibeklioğlu, H. (2020) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-020-00347-7 · Cited by 42

Attention-Enhanced Multimodal Learning for Conceptual Design Evaluations

Song, B., Miller, S. R., & Ahmed, F. (2023) · Journal of Mechanical Design · doi:10.1115/1.4056669 · Cited by 46

Efficient Driver Anomaly Detection via Conditional Temporal Proposal and Classification Network

Su, L., Sun, C., Cao, D., & Khajepour, A. (2022) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3158480 · Cited by 38

Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications

Mena, F., Arenas, D., Nuske, M., & Dengel, A. R. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3361556 · Cited by 38

Multilevel Sensor Fusion With Deep Learning

Vielzeuf, V., Lechervy, A., Pateux, S., & Jurie, F. (2018) · IEEE Sensors Letters · doi:10.1109/lsens.2018.2878908 · Cited by 35

Auto-weighting for Breast Cancer Classification in Multimodal Ultrasound

Wang, J., Miao, J., Yang, X., Li, R., Zhou, G., Huang, Y., Lin, Z., Xue, W., Jia, X., Zhou, J., et al. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59725-2_19 · Cited by 33

BM-NAS: Bilevel Multimodal Neural Architecture Search

Yin, Y., Huang, S., & Zhang, X. D. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i8.20872 · Cited by 35

On-the-Fly Modulation for Balanced Multimodal Learning

Wei, Y., Hu, D., Du, H., & Wen, J.-R. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3468315 · Cited by 30

Deep learning with convex probe endobronchial ultrasound multimodal imaging: A validated tool for automated intrathoracic lymph nodes diagnosis

Dai, W., Sun, J., Li, J., Zhi, X., Chen, J., Wang, L., Xu, M., & Xiong, H. (2021) · Endoscopic Ultrasound · doi:10.4103/eus-d-20-00207 · Cited by 32

Multi-View And Multi-Modal Event Detection Utilizing Transformer-Based Multi-Sensor Fusion

Yasuda, M., Ohishi, Y., Saito, S., & Harado, N. (2022) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp43922.2022.9746006 · Cited by 25

A Framework to Evaluate Fusion Methods for Multimodal Emotion Recognition

Peña, D., Aguilera, A., Dongo, I., Heredia, J., & Cardinale, Y. (2023) · IEEE Access · doi:10.1109/access.2023.3240420 · Cited by 26

MultiBench: Multiscale Benchmarks for Multimodal Representation Learning

Liang, P. P., Lyu, Y., Fan, X., Wu, Z., Cheng, Y., Wu, J., Chen, L., Wu, P., Lee, M. A., Zhu, Y., et al. (2021) · arXiv · doi:10.48550/arxiv.2107.07502 · Cited by 85

Deep multimodal learning for cross-modal retrieval: One model for all tasks

Beltrán, L. V. B., Caicedo, J. C., Journet, N., Coustaty, M., Lecellier, F., & Doucet, A. (2021) · Pattern Recognition Letters · doi:10.1016/j.patrec.2021.02.021 · Cited by 21

DC-NAS: Divide-and-Conquer Neural Architecture Search for Multi-Modal Classification

Liang, X., Fu, P., Guo, Q. J., Zheng, K., & Qian, Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i12.29281 · Cited by 21

HateThaiSent: Sentiment-Aided Hate Speech Detection in Thai Language

Maity, K., Poornash, A. S., Bhattacharya, S., Phosit, S., Kongsamlit, S., Saha, S., & Pasupa, K. (2024) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2024.3376958 · Cited by 22

Multilabel Genre Prediction Using Deep-Learning Frameworks

Ünal, F. Z., Güzel, M. S., Bostancı, E., Açıcı, K., & Aşuroğlu, T. (2023) · Applied Sciences · doi:10.3390/app13158665 · Cited by 21

MSMFN: An Ultrasound Based Multi-Step Modality Fusion Network for Identifying the Histologic Subtypes of Metastatic Cervical Lymphadenopathy

Meng, Z., Zhu, Y., Pang, W., Tian, J., Nie, F., & Wang, K. (2022) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2022.3222541 · Cited by 18

Dual-branch hybrid network for lesion segmentation in gastric cancer images

He, D., Zhang, Y., Huang, H., Si, Y., Wang, Z., & Li, Y. (2023) · Scientific Reports · doi:10.1038/s41598-023-33462-y · Cited by 18

Revisiting spatio-temporal layouts for compositional action recognition

Radevski, G., Moens, M., & Tuytelaars, T. (2021) · British Machine Vision Conference (BMVC) · doi:10.5244/c.35.278 · Cited by 26

CoDF-Net: coordinated-representation decision fusion network for emotion recognition with EEG and eye movement signals

Gong, X., Dong, Y., & Zhang, T. (2023) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-023-01964-w · Cited by 17

Transfer Learning for Optical and SAR Data Correspondence Identification With Limited Training Labels

Zhang, M., Li, W., Tao, R., & Wang, S. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3044643 · Cited by 16

Multi-label movie genre classification based on multimodal fusion

Cai, Z.-H., Ding, H., Wu, J., Xi, Y., Wu, X., & Cui, X. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16121-2 · Cited by 16

Negative Review or Complaint? Exploring Interpretability in Financial Complaints

Das, S., Singh, A., Saha, S., & Maurya, A. (2024) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2023.3338357 · Cited by 16

An information bottleneck approach for feature selection

Zhang, Q., Lu, M., Yu, S., Xin, J., & Chen, B. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111564 · Cited by 16

CrisisKAN: Knowledge-Infused and Explainable Multimodal Attention Network for Crisis Event Classification

Gupta, S., Saini, N., Kundu, S., & Das, D. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56060-6_2 · Cited by 19

Hierarchical Scale Awareness for object detection in Unmanned Aerial Vehicle Scenes

Wang, S., Wan, C., Yan, J., Li, S., Sun, T., Chi, J., Yang, G., Chen, C., & Yu, T. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.112487 · Cited by 14

Learning to Rebalance Multi-Modal Optimization by Adaptively Masking Subnetworks

Yang, Y., Pan, H., Jiang, Q.-Y., Xu, Y., & Tang, J. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3547417 · Cited by 20

Multimodal Multitask Emotion Recognition using Images, Texts and Tags

Fortin, M. P., & Chaib-draa, B. (2019) · doi:10.1145/3326459.3329165 · Cited by 13

Copula-Based Data Augmentation on a Deep Learning Architecture for Cardiac Sensor Fusion

Silva, D., Leonhardt, S. K., & Antink, C. H. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.3040551 · Cited by 13

N24News: A New Dataset for Multimodal News Classification

Wang, Z., Xu, S., Zhang, X., & Yang, J. (2022) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/5c2xbka7swxq · Cited by 29

Handling unexpected inputs: incorporating source-wise out-of-distribution detection into SAR-optical data fusion for scene classification

Gawlikowski, J., Saha, S., Niebling, J., & Zhu, X. X. (2023) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/s13634-023-01008-z · Cited by 12

ACF: An Adaptive Compression Framework for Multimodal Network in Embedded Devices

Cai, Q., Liu, X., Zhang, K., Xie, X. N., Tong, X., & Li, K. (2023) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2023.3303350 · Cited by 15

FedMMR: Multi-Modal Federated Learning via Missing Modality Reconstruction

Wang, S., Qu, Z., Liu, Y., Kan, S., Liang, Y., & Wang, J. (2024) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme57554.2024.10688162 · Cited by 12

Multimodal Semantic Consistency-Based Fusion Architecture Search for Land Cover Classification

Li, X., Lei, L., Zhang, C., & Kuang, G. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3193273 · Cited by 12

Language-Model-Based Paired Variational Autoencoders for Robotic Language Learning

Özdemir, O., Kerzel, M., Weber, C., Lee, J. H., & Wermter, S. (2022) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2022.3204452 · Cited by 12

Modality-Specific Learning Rate Control for Multimodal Classification

Fujimori, N., Endo, R., Kawai, Y., & Mochizuki, T. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-41299-9_32 · Cited by 12

A multiscale neural architecture search framework for multimodal fusion

Lv, J., Sun, Y., Ye, Q., Feng, W., & Lv, J. (2024) · Information Sciences · doi:10.1016/j.ins.2024.121005 · Cited by 12

Depression detection in read and spontaneous speech: A Multimodal approach for lesser-resourced languages

Daly, K., & Olukoya, O. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.107959 · Cited by 13

Chameleon: A Multimodal Learning Framework Robust to Missing Modalities

Liaqat, M. I., Nawaz, S., Zaheer, M. Z., Saeed, M. S., Sajjad, H., Schepper, T. D., Nandakumar, K., Khan, M. H., Gallo, I., & Schedl, M. (2025) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-025-00370-y · Cited by 16

MULTI-MODAL DEEP LEARNING WITH SENTINEL-3 OBSERVATIONS FOR THE DETECTION OF OCEANIC INTERNAL WAVES

Drees, L., Kusche, J., & Roscher, R. (2020) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-v-2-2020-813-2020 · Cited by 11

A comprehensive survey on image fusion: Which approach fits which need

Bernardi, G., Brisebarre, G., Roman, S., Ardabilian, M., & Dellandréa, E. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103594 · Cited by 15

COMO: Efficient Deep Neural Networks Expansion With COnvolutional MaxOut

Zhao, B., Xiong, H., Bian, J., Guo, Z., Xu, C., & Dou, D. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3002614 · Cited by 10

Multimodal Fusion Refiner Networks

Sankaran, S., Yang, D., & Lim, S.-N. (2021) · arXiv · doi:10.48550/arxiv.2104.03435 · Cited by 10

TransRNAm: Identifying Twelve Types of RNA Modifications by an Interpretable Multi-Label Deep Learning Model Based on Transformer

Chen, T., Wu, T., Pan, D., Xie, J., Jin, Z. X., Wang, X., Quan, L., & Lyu, Q. (2023) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2023.3307419 · Cited by 9

Multi-Scale Features Are Effective for Multi-Modal Classification: An Architecture Search Viewpoint

Fu, P., Liang, X., Qian, Y., Guo, Q. J., Zhang, Y., Huang, Q., & Tang, K. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3470996 · Cited by 9

Narrowband Radar Automatic Target Recognition Based on a Hierarchical Fusing Network With Multidomain Features

Gao, Y., Zhou, Y., Wang, Y., & Zhuo, Z. (2020) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2020.2993039 · Cited by 9

Enhancing Multimodal Learning via Hierarchical Fusion Architecture Search With Inconsistency Mitigation

Long, K., Xie, G., Ma, L., Li, Q., Huang, M., Lv, J., & Lu, Z. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3599673 · Cited by 8

Investigate How Market Behaves: Toward an Explanatory Multitasking Based Analytical Model for Financial Investments

Das, S., Chowdhury, U., Lijin, N. S., Deep, A., Saha, S., & Maurya, A. (2024) · IEEE Access · doi:10.1109/access.2024.3369033 · Cited by 8

Using DeepSignalingFlow to mine signaling flows interpreting mechanism of synergy of cocktails

Zhang, H., Chen, Y., Payne, P., & Li, F. (2024) · npj Systems Biology and Applications · doi:10.1038/s41540-024-00421-w · Cited by 15

Enhancing Acute Bilirubin Encephalopathy Diagnosis with Multi-Modal MRI: A Deep Learning Approach

Zhang, H., & Xia, S. (2024) · Applied Sciences · doi:10.3390/app14062464 · Cited by 7

A Multi-Stream Recurrent Neural Network for Social Role Detection in Multiparty Interactions

Zhang, L., & Radke, R. J. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.2992394 · Cited by 8

Modeling the nonlinear responses of soft network materials assisted by masked-fusion artificial neural network

Cao, S., Wang, H., Lai, Y., Bo, R., & Feng, X. (2023) · Materials Today Communications · doi:10.1016/j.mtcomm.2023.106013 · Cited by 7

TDSF-Net: Tensor Decomposition-Based Subspace Fusion Network for Multimodal Medical Image Classification

Zhang, Y., Xu, G., Zhao, M. Y., Wang, H., Shi, F., & Chen, S. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3541170 · Cited by 6

Exploring Deep Learning-Based Multi-modality Fusion Approaches in Classification of Lung Diseases: A Review

Shingan, G. G., & Ranjan, P. (2025) · Learning and analytics in intelligent systems · doi:10.1007/978-3-031-82706-8_10 · Cited by 6

Cross-Aligned Fusion For Multimodal Understanding

Rajora, A., Gupta, S., & Kundu, S. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00559 · Cited by 6

Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM approaches

Al‐bayati, J. S. H., & Üstündağ, B. B. (2020) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2020.013329 · Cited by 6

Multimodal dynamic graph convolutional network for crowdfunding success prediction

Cai, Z.-H., Ding, H., Xu, M., & Cui, X. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.111313 · Cited by 7

Deep Stacked Ensemble Recommender

Otunba, R., Rufai, R. A., & Lin, J. (2019) · International Conference on Scientific and Statistical Database Management · doi:10.1145/3335783.3335809 · Cited by 6

Fusion of LiDAR and Camera Images in End-to-end Deep Learning for Steering an Off-road Unmanned Ground Vehicle

Warakagoda, N. D., Dirdal, J. A., & Faxvaag, E. (2019) · International Conference on Information Fusion (FUSION) · doi:10.23919/fusion43075.2019.9011341 · Cited by 6

A central multimodal fusion framework for outdoor scene image segmentation

Zhang, Y., Morel, O., Seulin, R., Mériaudeau, F., & Sidibé, D. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-020-10357-y · Cited by 5

Optimizing Movie Selections: A Multi-Task, Multi-Modal Framework with Strategies for Missing Modality Challenges

Raj, S., Agrawal, P., Saha, S., Singh, B., & Pedanekar, N. (2024) · ACM Symposium on Applied Computing · doi:10.1145/3605098.3635947 · Cited by 5

LandGPT: a multimodal large language model for parcel-level land use classification with multi-source data

Zhu, G., Tang, M., Ma, Y., Hu, Z., Yu, C., Zhang, X., Hu, H., Guan, Q., & Yao, Y. (2025) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2025.2506533 · Cited by 6

Feature Stacking Fusion in Multimodal Neural Architecture Search

Long, K., Ma, L., Gao, Y., & Yu, G. (2024) · International Conference on Data-driven Optimization of Complex Systems (DOCS) · doi:10.1109/docs63458.2024.10704481 · Cited by 6

MMRDF: An improved multitask multi‐modal rumor detection framework

Jiang, F., Liang, G., Yang, J., & Chen, L. (2023) · Electronics Letters · doi:10.1049/ell2.12811 · Cited by 5

A Model-Level Fusion-Based Multi-Modal Object Detection and Recognition Method

Chen, G., & Zhang, L. (2023) · Asian Conference on Artificial Intelligence Technology (ACAIT) · doi:10.1109/acait60137.2023.10528389 · Cited by 5

SSPRA: A Robust Approach to Continuous Authentication Amidst Real-World Adversarial Challenges

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Diagnosis of Lung Cancer Using Endobronchial Ultrasonography Image Based on Multi-Scale Image and Multi-Feature Fusion Framework

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