Results 271 to 280 of about 4,404,768 (300)

Describing Videos using Multi-modal Fusion

Proceedings of the 24th ACM international conference on Multimedia, 2016
Describing videos with natural language is one of the ultimate goals of video understanding. Video records multi-modal information including image, motion, aural, speech and so on. MSR Video to Language Challenge provides a good chance to study multi-modality fusion in caption task. In this paper, we propose the multi-modal fusion encoder and integrate
Qin Jin, Jia Chen 0001, Shizhe Chen, Yifan Xiong 0001, Alexander G. Hauptmann   +4 more
openaire   +2 more sources

Improved Sentiment Classification by Multi-Modal Fusion

2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService), 2017
Sentiment Analysis (SA) is the task of detecting people's emotions from their written text. Many algorithms have been studied for that purpose, with different authors claiming one or the other as better by a given metric. In recent years, the focus of SA has shifted to online text and microblog text, messages so short that good analysis becomes ...
Lige Gan, Rachid Benlamri, Richard Khoury   +2 more
openaire   +2 more sources

Multi-modality Fusion Network for Action Recognition

2018
Deep neural networks have outperformed many traditional methods for action recognition on video datasets, such as UCF101 and HMDB51. This paper aims to explore the performance of fusion of different convolutional networks with different dimensions. The main contribution of this work is multi-modality fusion network (MMFN), a novel framework for action ...
Kai Huang, Zheng Qin 0003, Kaiping Xu, Shuxiong Ye, Guolong Wang 0001   +4 more
openaire   +1 more source

Multi-modal Image Fusion with KNN Matting

2014
A single captured image of a scene is usually insufficient to reveal all the details due to the imaging limitations of single senor. To solve this problem, multiple images capturing the same scene with different sensors can be combined into a single fused image which preserves the complementary information of all input images.
Xia Zhang, Hui Lin, Xudong Kang, Shutao Li 0001   +3 more
openaire   +2 more sources

Fuzzy classification for multi-modality image fusion

Proceedings of 1st International Conference on Image Processing, 2002
In the framework of fuzzy set theory, we propose: (i) a classification scheme for multi-modality image fusion, where membership degrees to a class issued from several images are combined before taking a decision, (ii) a classification of fusion operators, depending on their behaviour. >
openaire   +1 more source

Multi-modal Fusion

Information Sciences, 2018
Huaping Liu 0001, Amir Hussain 0001, Shuliang Wang 0001   +2 more
openaire   +1 more source

Diffusion-driven multi-modality medical image fusion

Medical & Biological Engineering & Computing
Multi-modality medical image fusion (MMIF) technology utilizes the complementarity of different modalities to provide more comprehensive diagnostic insights for clinical practice. Existing deep learning-based methods often focus on extracting the primary information from individual modalities while ignoring the correlation of information distribution ...
Jiantao Qu, Dongjin Huang, Yongsheng Shi, Jinhua Liu 0002, Wen Tang 0004   +4 more
openaire   +2 more sources

MOFA: A novel dataset for Multi-modal Image Fusion Applications

Information Fusion, 2023
Puhong Duan, Xudong Kang, Haibo Liu
exaly  

Multi-modal Imaging and Image Fusion

2011
In vivo imaging in small animals is playing an increasingly important role in the understanding of basic physiological processes, in the study of disease and evaluation of therapies; in addition to providing unique information in its own right, it also provides an essential bridge between invasive techniques, which often require postmortem analysis ...
openaire   +1 more source

Memory based fusion for multi-modal deep learning

Information Fusion, 2021
Darshana Priyasad, Simon Denman, Tharindu Fernando   +2 more
exaly