Results 51 to 60 of about 43,272 (165)

MFFNet: a wavelet transform-based multimodal frequency fusion network for remote sensing semantic segmentation

GIScience & Remote Sensing
The use of multimodal data for semantic segmentation in remote sensing has attracted considerable interest, as it enables the integration of complementary information from various sensors. However, conventional multimodal fusion methods primarily operate
Chao Li, Haitao Lyu, Weipeng Jing, Ye Yuan, Guangliang Cheng   +4 more
doaj   +1 more source

Multimodal Biometric Fusion: Performance under Spoof Attacks

Journal of Intelligent Systems, 2011
Biometrics is essentially a pattern recognition system that recognizes an individual using their unique anatomical or behavioral patterns such as face, fingerprint, iris, signature etc.
Akhtar Zahid, Rizwan Mohammed, Kale Sandeep   +2 more
doaj   +1 more source

Text-Image Gated Fusion Mechanism for Multimodal Aspect-based Sentiment Analysis [PDF]

Jisuanji kexue
Multimodal aspect-based sentiment analysis is an emerging task in multimodal sentiment analysis field,which aims to identify the sentiment of each given aspect in text and image.Although recent research on multimodal sentiment analysis has made ...
ZHANG Tianzhi, ZHOU Gang, LIU Hongbo, LIU Shuo, CHEN Jing
doaj   +1 more source

Multimodal Fusion SLAM With Fourier Attention

IEEE Robotics and Automation Letters
Visual SLAM is particularly challenging in environments affected by noise, varying lighting conditions, and darkness. Learning-based optical flow algorithms can leverage multiple modalities to address these challenges, but traditional optical flow-based visual SLAM approaches often require significant computational resources.To overcome this limitation,
Youjie Zhou, Guofeng Mei, Yiming Wang 0002, Yi Wan 0002, Fabio Poiesi   +4 more
openaire   +3 more sources

Federated high order tensor fusion for privacy preserving multimodal social media analysis.

PLoS ONE
The rapid evolution of social networks has positioned multimodal content, including text, images, and audio, as a pivotal medium for self-expression and public sentiment analysis.
Li Wan, Bin Zhang
doaj   +1 more source

Sentiment Classification Method Based on Stepwise Cooperative Fusion Representation [PDF]

Jisuanji kexue
The goal of multimodal sentiment analysis is to perceive and understand human emotions through various heteroge-neous modalities,such as language,video,and audio.However,there are complex correlations between different modalities.Most existing methods ...
GAO Long, LI Yang, WANG Suge
doaj   +1 more source

Multimodality and Multiresolution Image Fusion.

, 2012
Standard multiresolution image fusion of multimodal images may yield an output image with artifacts due to the occurrence of opposite contrast in the input images. Equal but opposite contrast leads to noisy patches, instable with respect to slight changes in the input images.
P.M. de Zeeuw (Paul), E.J.E.M. Pauwels (Eric), J. Han (Jungong )   +2 more
openaire   +1 more source

Orthogonal Sequential Fusion in Multimodal Learning

2025 28th International Conference on Information Fusion (FUSION)
The integration of data from multiple modalities is a fundamental challenge in machine learning, encompassing applications from image captioning to text-to-image generation. Traditional fusion methods typically combine all inputs concurrently, which can lead to an uneven representation of the modalities and restricted control over their integration. In
Labbaki, S, Minary, P
openaire   +2 more sources

A multimodal transformer-based visual question answering method integrating local and global information.

PLoS ONE
Addressing the limitations in current visual question answering (VQA) models face limitations in multimodal feature fusion capabilities and often lack adequate consideration of local information, this study proposes a multimodal Transformer VQA network ...
Cuiyang Huang, Zihan Hu
doaj   +1 more source

LGCDF: Label-Guided Contrastive Disentanglement Fusion of Sensitive Attribute-Free Representations for Fair Multimodal Sentiment Analysis

Applied Sciences
Multimodal sentiment analysis (MSA) has emerged as a prominent research frontier, enabling a comprehensive understanding of complex human emotions through the synergistic integration of heterogeneous multimodal signals.
Rongfei Chen, Xinming Zhang, Siwei Cheng, Tingting Zhang, Hanlin Zhang, Wei Zhang   +5 more
doaj   +1 more source