Results 251 to 260 of about 97,244 (288)

Multi-modal Data Fusion: A Description

2004
Clustering groups records that are similar to each other into the same group, and those that are less similar into different groups. Clustering data of mixed types is difficult due to different data characteristics. Extending Gower’s metric for nominal and ordinal data is incorporated into an agglomerative hierarchical clustering algorithm to cluster ...
Sarah Coppock, Lawrence J. Mazlack
openaire   +1 more source

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   +1 more source

Multi-modal medical image fusion using 2DPCA

2017 2nd International Conference on Image, Vision and Computing (ICIVC), 2017
Principal Component Analysis is a dimension reduction technique that is widely used in the area of image fusion, classification and face recognition. It cannot be applied on two-dimensional images directly, instead, two-dimensional images must be transformed into one-dimensional vectors prior to applying PCA.
Qamar Nawaz, Xiao Bin, Li Weisheng, Isma Hamid   +3 more
openaire   +1 more source

Multi-modal biometrics fusion: beyond optimal weighting

7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002., 2004
The multivariate polynomials model provides an effective way to describe complex nonlinear input-output relationships as it is tractable for optimization, sensitivity analysis, and prediction of confidence intervals. However, for high dimensional and high order problems, multivariate polynomial regression becomes impractical due to its prohibitive ...
K.-A. Toh, null Wei-Yun Yau
openaire   +1 more source

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, Kaiping Xu, Shuxiong Ye, Guolong Wang   +4 more
openaire   +1 more source

Multi-modal decision fusion for continuous authentication

Computers & Electrical Engineering, 2015
Display Omitted Behavioral biometrics: keystroke dynamics, mouse movement, stylometry.A parallel binary decision fusion architecture with 11 sensors.A dataset collected from 67 users each working in an office environment for a week.Achieve below 1% error rates (FAR, FRR) after only 30s of activity.Characterize robustness of system to adversarial ...
Lex Fridman, Ariel Stolerman, Sayandeep Acharya, Patrick Brennan, Patrick Juola, Rachel Greenstadt, Moshe Kam   +6 more
openaire   +1 more source

Fast saliency-aware multi-modality image fusion

Neurocomputing, 2013
This paper proposes a saliency-aware fusion algorithm for integrating infrared (IR) and visible light (ViS) images (or videos) with the aim to enhance the visualization of the latter. Our algorithm involves saliency detection followed by a biased fusion. The goal of the saliency detection is to generate a saliency map for the IR image, highlighting the
Han, Jungong, Pauwels, Eric J., de Zeeuw, Paul   +2 more
openaire   +2 more sources

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

Fusion of multi-modality volumetric medical imagery

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997), 2003
Ongoing efforts at our laboratory have targeted the development of techniques for fusing medical imagery of various modalities (i.e. MRI, CT, PET, SPECT, etc.) into single image products. Past results have demonstrated the potential for user performance improvements and workload reduction.
M. Aguilar, J.R. New
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   +3 more
openaire   +1 more source