Deep multimodal fusion for semantic image segmentation: A survey

Attention Is All You Need

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SIN-Seg: A joint spatial-spectral information fusion model for medical image segmentation

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A Review of Fake News Detection Models: Highlighting the Factors Affecting Model Performance and the Prominent Techniques Used

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CAFseg: A Semantic segmentation network with cross aggregation fusion strategy for RGB-thermal semantic segmentation

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GEOMAPI: Processing close-range sensing data of construction scenes with semantic web technologies

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HCFS3D: Hierarchical coupled feature selection network for 3D semantic and instance segmentation

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MEAI: an artificial intelligence platform for predicting distant and lymph node metastases directly from primary breast cancer

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MAFNet: A deep multi-scale attentive fusion network for virtual osteotomy of maxillofacial bones in CT images containing metal artifacts

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Transfer Learning-Driven Cattle Instance Segmentation Using Deep Learning Models

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DF2RQ: Dynamic Feature Fusion via Region-Wise Queries for Semantic Segmentation of Multimodal Remote Sensing Data

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Comparison of Asphalt Pavement Crack Segmentation Based on Different Fusion Methods of RGB Images and Thermal Images

Yu, Y., Kang, S., He, D., Kumar, R., Singh, V., & Wang, Z. (2025) · Journal of Transportation Engineering Part B Pavements · doi:10.1061/jpeodx.pveng-1747 · Cited by 7

RGB-Thermal cameras calibration based on Maximum Index Map

Wei, J., Zou, Z., Lai, W., Du, J., Zhao, J., Liu, Z., & Wang, S. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110234 · Cited by 7

MMF-CNN: a multimodal fusion CNN network for winter wheat extraction incorporating active and passive time series data

Chen, J., Han, H., Xu, M., Wan, J., & Liu, S. (2024) · International Journal of Remote Sensing · doi:10.1080/01431161.2024.2318773 · Cited by 7

Transferring Multi-Modal Domain Knowledge to Uni-Modal Domain for Urban Scene Segmentation

Liu, P., Ge, Y., Duan, L., Li, W., Luo, H., & Lv, F. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3382880 · Cited by 8

Image Based River Navigation System of Catamaran USV with Image Semantic Segmentation

Yang, P., Song, C., Chen, L., & Cui, W. (2022) · WRC Symposium on Advanced Robotics and Automation (WRC SARA) · doi:10.1109/wrcsara57040.2022.9903932 · Cited by 7

Exploring fusion techniques in U-Net and DeepLab V3 architectures for multi-modal land cover classification

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Enhancing UAS-Based Multispectral Semantic Segmentation Through Feature Engineering

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Self-Supervised Visual Odometry Based on Scene Appearance-Structure Incremental Fusion

Fu, F., Yang, J., Ma, J., & Zhang, J. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3559077 · Cited by 6

Explainable Multi-Modal Fusion-Based Federated Learning for Mortality Prediction in Energy-Constrained Healthcare Systems

Bibi, M., Ahmad, R., Rizwan, A., Khan, A. N., Khan, Q. W., & Kim, D.-H. (2026) · IEEE Access · doi:10.1109/access.2025.3650610 · Cited by 9

COMBINING IMAGE AND POINT CLOUD SEGMENTATION TO IMPROVE HERITAGE UNDERSTANDING

Bassier, M., Mazzacca, G., Battisti, R., Malek, S., & Fabio Remondino, A. (2024) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xlviii-2-w4-2024-49-2024 · Cited by 6

SSR-2D: Semantic 3D Scene Reconstruction From 2D Images

Huang, J., Artemov, A., Chen, Y., Zhi, S., Xu, K., & Nießner, M. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3410032 · Cited by 6

Dual-Modal Illumination System for Defect Detection of Aircraft Glass Canopies

Li, Z., Yao, Y., Wen, R., & Liu, Q. (2024) · Sensors · doi:10.3390/s24206717 · Cited by 8

Deep learning for multi-modal data fusion in IoT applications

Saghir, A., Akbar, A., Zafar, A., & Hassan, A. (2025) · Mehran University Research Journal of Engineering and Technology · doi:10.22581/muet1982.3171 · Cited by 6

Reciprocal cross-modal guidance for liver lesion segmentation from multiple phases under incomplete overlap

Yu, W., Wang, M., Zhang, Y., & Zhao, L. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105561 · Cited by 6

NaMa: Neighbor-Aware Multi-Modal Adaptive Learning for Prostate Tumor Segmentation on Anisotropic MR Images

Meng, R.-Q., Zhang, X., Huang, S., Gu, Y., Liu, G.-Q., Wu, G., Wang, N., Sun, K., & Shen, D.-G. (2024) · AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i5.28215 · Cited by 5

Attention-Based Fusion of Ultrashort Voice Utterances and Depth Videos for Multimodal Person Identification

Moufidi, A., Rousseau, D., & Rasti, P. (2023) · Sensors · doi:10.3390/s23135890 · Cited by 6

A novel 6DoF pose estimation method using transformer fusion

Wang, H., Zhang, H., Liu, W., Hu, Z., Gao, H., Lv, W., & Gu, X. D. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111413 · Cited by 5

A memory-tree driven network for multi-view fusion anomaly detection

Liu, X., Wu, C., Zhang, H., & Wang, L. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.112106 · Cited by 5

Domain-Knowledge-Guided Multisource Fusion Network for Small Water Bodies Mapping Using PlanetScope Multispectral and Google Earth RGB Images

Zhou, P., Li, X., Zhang, Y., Wang, Y., Li, Y., Li, X., Zhou, C., Shen, L., & Du, Y. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3509712 · Cited by 5

Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data

Dimitrovski, I., Spasev, V., & Kitanovski, I. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-86162-8_8 · Cited by 5

A Multiscale Vision Transformer-Based Multimodal GeoAI Model for Mapping Arctic Permafrost Thaw

Li, W., Hsu, C.-Y., Wang, S., Gu, Z., Yang, Y., Rogers, B. M., & Liljedahl, A. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3564310 · Cited by 6

Interpretable multimodal learning for tumor protein-metal binding: Progress, challenges, and perspectives

Liu, X., Rastegari, S., Huang, Y., Cheong, S. C., Liu, W., Zhao, W., Tian, Q., Wang, H., Guo, Y., Zhou, S., et al. (2025) · Methods · doi:10.1016/j.ymeth.2025.07.004 · Cited by 5

Bimodal defect segmentation with Geometric Prior-supported Anti-imbalance Learning for pavement defect evaluation and repair

Wang, Y., Song, K., Liu, Y., Li, T., Yan, Y., & Carneiro, G. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.106497 · Cited by 4

Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification

Tschuchnig, M., Gadermayr, M., & Djemal, K. (2025) · International Conference on Image Processing Theory, Tools and Applications (IPTA) · doi:10.1109/ipta66025.2025.11222017 · Cited by 4

A comprehensive survey on magnetic resonance image reconstruction

Kui, X., Fan, Z., Ji, Z., Li, Q., Liu, C., Si, W., & Zou, B. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105832 · Cited by 4

Deep learning-based astronomical multimodal data fusion: A comprehensive review

Shao, W., Fan, D., Cui, C., Xu, Y., Wei, S., & Lyu, X. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.104103 · Cited by 8

Multi‐focal channel attention for medical image segmentation

Jowair, H. A., Alsulaiman, M., & Muhammad, G. (2024) · Expert Systems · doi:10.1111/exsy.13588 · Cited by 4

Panoramic sales insight: Using multimodal fusion to improve the effectiveness of flash sales

Wang, H., Chen, Z., Fang, M., Wang, Y., & Liu, F. (2025) · Decision Support Systems · doi:10.1016/j.dss.2025.114401 · Cited by 7

A Neighbor-Sensitive Multi-Modal Flexible Learning Framework for Improved Prostate Tumor Segmentation in Anisotropic MR Images

Meng, R.-Q., Chen, J.-L., Sun, K., Chen, Q., Zhang, X., Dai, L., Gu, Y., Wu, G., & Shen, D. (2025) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2025.3562766 · Cited by 4

Multimodal SAM-Adapter for Semantic Segmentation

Curti, I., Ramirez, P. Z., Petrelli, A., & Stefano, L. D. (2025) · IEEE Access · doi:10.1109/access.2025.3609640 · Cited by 5

CMFNet: a cross-dimensional modal fusion network for accurate vessel segmentation based on OCTA data

Wang, S., Yu, X., Wu, H., Wang, Y., & Wu, C. (2024) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-024-03256-z · Cited by 4

Mineral segmentation using electron microscope images and spectral sampling through multimodal graph neural networks

Repka, S., Reich, B., Zolotarev, F., Eerola, T., & Zemčík, P. (2025) · Pattern Recognition Letters · doi:10.1016/j.patrec.2025.04.012 · Cited by 4

FusionSAM: Visual Multi-Modal Learning with Segment Anything Model

Li, D., Xie, W., Cao, M., Wang, Y., Zhang, Y., Fang, L., Li, Y., & Xu, C. (2025) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3711896.3736973 · Cited by 4

Dual attention-based deep learning approach for building segmentation of remote sensing images

Srivastava, N., & Jain, K. K. (2023) · Remote Sensing Technologies and Applications in Urban Environments · doi:10.1117/12.2684330 · Cited by 4

A Multimodal Fusion System for Object Identification in Point Clouds with Density and Coverage Differences

Bernal, D. F. Q., Kern, J., & Urrea, C. (2024) · Processes · doi:10.3390/pr12020248 · Cited by 4

Inspect quantitative signals in placental histopathology: Computer-assisted multiple functional tissues identification through multi-model fusion and distillation framework

Liu, Y., Zhang, L., Gu, M., Xiao, Y., Yu, T., Tao, X., Zhang, Q., Wang, Y., Shen, D. G., & Li, Q. (2024) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2024.102482 · Cited by 3

Multimodal Data Fusion System for Accurate Identification of Impact Points on Rocks in Mining Comminution Tasks

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Project-and-fuse: Improving RGB-D semantic segmentation via graph convolution networks

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Deep insights into cognitive decline: A survey of leveraging non-intrusive modalities with deep learning techniques

Ortiz-Pérez, D., Benavent-Lledó, M., Garcia-Rodriguez, J., Tomás, D., & Vizcaya-Moreno, M. F. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.113787 · Cited by 6

CH3 photo-fragmentation laser-induced fluorescence for turbulent flame diagnosis

Carter, C. D., McGann, B., Eckhart, S. D., & Nilsson, S. (2025) · Combustion and Flame · doi:10.1016/j.combustflame.2025.114529 · Cited by 3

DeepSyncNet:Deep synchronized fusion network for EEG-fNIRS multimodal brain-computer interfaces

Li, H. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.109100 · Cited by 4

A multi-scale CNN-GRU fusion model with stationary wavelet transform for 14-day ahead dam water level prediction

Ng, K. W., Huang, Y. F., Koo, C. H., El‐Shafie, A., Sherif, M. M., & Ahmed, A. N. (2025) · Scientific Reports · doi:10.1038/s41598-025-24880-1 · Cited by 3

Sensing Technologies for Hand Gesture Recognition in Human–Robot Interaction: A Review

Liang, B., Li, N., Li, G., Huang, J., Yu, Z., & Zhao, X. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3635622 · Cited by 5

Fully Exploiting Vision Foundation Model's Profound Prior Knowledge for Generalizable RGB-Depth Driving Scene Parsing

Guo, S., Wen, T., Liu, C.-W., Chen, Q., & Fan, R. (2026) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2025.3650682 · Cited by 3

BATFNet: Boundary-Aware Transformer Fusion Network for RGB-DSM Semantic Segmentation of Remote Sensing Images

Tong, Y., Tang, M., Zhang, Y., Huang, Y., Huang, J., He, Y., Liu, Y., Akpokodje, E., & Zheng, D. (2026) · Sensors · doi:10.3390/s26103205 · Cited by 3

Enhancing Visual Feedback Control through Early Fusion Deep Learning

Botezatu, A.-P., Ferariu, L. E., & Burlacu, A. (2023) · Entropy · doi:10.3390/e25101378 · Cited by 3

Optimization of Deep Learning Parameters for Magneto-Impedance Sensor in Metal Detection and Classification

Kim, H., Chae, H., Kwon, S., & Lee, S.-H. (2023) · Sensors · doi:10.3390/s23229259 · Cited by 3

Segmenting Anything in the Dark via Depth Perception

Liu, P., Deng, J., Duan, L., Li, W., & Lv, F. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3557612 · Cited by 5

Application on the Loop of Multimodal Image Fusion: Trends on Deep-Learning Based Approaches

Guacho, G. K. B., Vallejo, P. X. M., Vintimilla, B. X., & Sappa, A. D. (2023) · International Conference on Pattern Recognition Systems (ICPRS) · doi:10.1109/icprs58416.2023.10179005 · Cited by 3

Dense orchard landscape mapping based on image merging with skeleton prediction

Pan, S., Niu, Z., Deng, J., Gao, W., Yan, Y., Zhou, M., & Han, W. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103578 · Cited by 3

Joint Semantic Segmentation of Optical and SAR Image in Hazy Environments via Cross-modal Information Rectification and Cross-attention Fusion

Fan, X., & Zhang, L. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889098 · Cited by 3

Speech-Based Estimation of Schizophrenia Severity Using Feature Fusion

Premananth, G., & Espy-Wilson, C. (2025) · IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW) · doi:10.1109/icasspw65056.2025.11011243 · Cited by 3

Fusing Convolutional Neural Networks with Segmentation for Brain Tumor Classification

Ferariu, L. E., & Neculau, E. D. (2021) · International Conference on System Theory, Control and Computing (ICSTCC) · doi:10.1109/icstcc52150.2021.9607260 · Cited by 3

Automatic MRI Lymph Node Annotation From CT Labels

Kundu, S., Iwahori, Y., Bhuyan, M. K., Bhatt, M., Kijsirikul, B., Wang, A., Ouchi, A., & Shimizu, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3535219 · Cited by 2

Learnable confidence-driven asymmetric attention fusion mechanism for PET/CT tumor segmentation

Diao, Z., Zhang, Y., Xu, Y. Y., Chen, X., & Sun, Z. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07313-8 · Cited by 2

FLAMES —Federated Learning for Advanced MEdical Segmentation

Savoia, M., Prezioso, E., & Piccialli, F. (2025) · Expert Systems · doi:10.1111/exsy.70090 · Cited by 2

A survey of federated learning-based gradient compression for internet of vehicles

Xing, L., Luo, Z., Gao, J., Deng, K., Wu, H., & Ma, H. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111662 · Cited by 2

A systematic review of semantic segmentation methods for histopathology images: a focused survey on breast, colon, and prostate cancers

Tan, D. I. T. M. H., Tan, X. J., Lim, L. L., Rahman, K. S. A., & Siet, J. J. W. (2025) · Applied Intelligence · doi:10.1007/s10489-025-06906-3 · Cited by 2

Poe2CLP: phrase-level attention and cross-modal semantic alignment for poem generate chinese landscape paintings

Peng, X., Sun, T., Hu, Q., Sun, Z., Xu, N., & Peng, J. (2025) · npj Heritage Science · doi:10.1038/s40494-025-02238-0 · Cited by 2

Anatomy-guided prompting with cross-modal self-alignment for whole-body PET-CT breast cancer segmentation

Huang, J., Yang, X., Liang, X., Chen, S., Sun, Y., Mok, G. S. P., Li, S., Wang, Y., & Tan, T. (2026) · Medical Image Analysis · doi:10.1016/j.media.2026.103956 · Cited by 2

Progress in multi-modal image semantic segmentation based on deep learning

Zhao, S., & Zhang, Q. (2023) · Journal of Image and Graphics · doi:10.11834/jig.220451 · Cited by 3

Multilevel-based algorithm for hyperspectral image interpretation

Qiu, S., Ye, H., Liao, X., Zhang, B., Zhang, M., & Zeng, Z. (2023) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2023.109033 · Cited by 2

IIMT-net: Poly-1 weights balanced multi-task network for semantic segmentation and depth estimation using interactive information

He, M., Yang, Z., Zhang, G., Long, Y., & Song, H. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.105109 · Cited by 2

View-aligned pixel-level feature aggregation for 3D shape classification

Xu, Y., Pan, S., Xu, R., & Ling, H. (2024) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2024.104098 · Cited by 2

Enhancing indoor place classification for mobile robots using RGB-D data and deep learning architectures

van Eden, B., & Botha, N. (2024) · MATEC Web of Conferences · doi:10.1051/matecconf/202440604002 · Cited by 2

An efficient deep learning strategy for real-time semantic segmentation of trees for embedded systems

Leroy, P., Abisset‐Chavanne, E., Pommier, R., & Montemurro, M. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111516 · Cited by 2

YOLO-FMEN: Pixel-Level Image Fusion-Based Nighttime Object Detection Network

Chen, Y.-T., & Da, F. (2025) · Chinese Control Conference (CCC) · doi:10.23919/ccc64809.2025.11179509 · Cited by 2

Visual Feedback Control using CNN Based Architecture with Input Data Fusion

Botezatu, A.-P., Ferariu, L. E., Burlacu, A., & Sauciuc, T.-A. (2022) · International Conference on System Theory, Control and Computing (ICSTCC) · doi:10.1109/icstcc55426.2022.9931843 · Cited by 2

Editorial: Special Issue on Recent Advances in Cognitive Learning and Data Analysis

Luo, B., Tang, J., & Liu, C. (2022) · Cognitive Computation · doi:10.1007/s12559-022-10019-1 · Cited by 2

TEXTURE-BASED SEPARATION TO REFINE BUILDING MESHES

Vermandere, J., Bassier, M., & Vergauwen, M. (2023) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-x-1-w1-2023-479-2023 · Cited by 1

AI powered road network prediction with fused low-resolution satellite imagery and GPS trajectory

Gengeç, N. E., Tarı, E., & Bağcı, U. (2024) · Earth Science Informatics · doi:10.1007/s12145-023-01201-6 · Cited by 1

Multimodal Learning

Škrlj, B. (2024) · SpringerBriefs in computer science · doi:10.1007/978-3-031-57016-2_6 · Cited by 1

Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinations

Yang, J., Chung, H., & Jang, I. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.113432 · Cited by 1

mmHand: Toward Pixel-Level-Accuracy Hand Localization Using a Single Commodity mmWave Device

Zhang, X., Li, Z., Xu, C., Song, L., Li, H., Xue, H., Wu, Y., & Xu, W. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3546560 · Cited by 1

Una revisión de fusión de datos multimodal: aplicaciones y condiciones adversas

Bernal, D., Héctor Kaschel, C., & Kern, J. (2025) · Inge CUC · doi:10.17981/ingecuc.21.1.2025.08 · Cited by 1

Two-Stage Dynamic Fusion Framework for Multimodal Classification Tasks

Ge, S., & Chen, Y. H. (2025) · INFORMS journal on computing · doi:10.1287/ijoc.2023.0448 · Cited by 1

Semantic-Aware Monostatic ISAC System with Dynamic Multimodal Fusion

Guo, J., Yang, J., Du, T., Wen, C.-K., & Jin, S. (2025) · IEEE/CIC International Conference on Communications in China (ICCC) · doi:10.1109/iccc65529.2025.11148970 · Cited by 1

Interpretable and Performant Multimodal Nasopharyngeal Carcinoma GTV Segmentation with Clinical Priors Guided 3D-Gaussian-Prompted Diffusion Model (3DGS-PDM)

Zhu, J., Ma, Z., Ren, G., & Cai, J. (2025) · Cancers · doi:10.3390/cancers17223660 · Cited by 1

CEASeg: Cross-modal Efficient Attention Semantic Segmentation Method for Remote Sensing Images

Zhang, H., Wang, Y., Zhang, Z., Qi, D., & Ding, W. (2025) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss55030.2025.11243864 · Cited by 1

Filling the Gaps: A Multitask Hybrid Multiscale Generative Framework for Missing Modality in Remote Sensing Semantic Segmentation

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Depth-guided cross-modal fusion and diffusion-based enhancement for robust pavement defect segmentation

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