Results 251 to 260 of about 2,643,411 (303)

Multimodal feature fusion for concreteness estimation

2022 25th International Conference on Information Fusion (FUSION), 2022
In recent years the idea of fusing diverse type of information has often been employed to solve various Deep Learning tasks. Whether these regard an NLP problem or a Machine Vision one, the concept of using more inputs of the same type has been the basis of many studies.
Incitti F., Snidaro L.
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Feature++: Cross dimension feature fusion for road detection

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
Road detection is a key component of Advanced Driving Assistance Systems, which provides valid space and candidate regions of objects for vehicles. Mainstream road detection methods have focused on extracting discriminative features. In this paper, we propose a robust feature fusion framework, called “Feature++”, which is combined with superpixel ...
Wenli He, Guo-Rong Cai, Zhun Zhong, Songzhi Su   +3 more
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Multiscale Feature Fusion for Face Identification

2017 3rd IEEE International Conference on Cybernetics (CYBCONF), 2017
Over the past 20 years, information fusion has seen rapid development and has been used in many applications, including pattern recognition and computer vision. Multi-modal biometrics is one form of information fusion where biometric information from different modes of input (e.g., finger print, iris image, face image) is fused in order to achieve ...
Xin Wei 0002, Hui Wang 0001, Huan Wan, Bryan W. Scotney   +3 more
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Feature Fusion Techniques

2015
Researcher introduced biometric system to improve the security because nowadays, the world is becoming more insecure. The term Biometrics is derived from the Greek composite words bio and metric. Bio means life and metric means to measure. Biometrics basically is a measure and analysis of human physiological and behavioral characteristics to identify ...
Koteswara Rao Anne, Swarna Kuchibhotla, Hima Deepthi Vankayalapati   +2 more
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Multi-Exposure Fusion with CNN Features

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
Multi-exposure fusion (MEF) is a widely used approach to high dynamic range imaging. The selection of features for fusion weight calculation is important to the performance of MEF. In this paper, we investigate the effectiveness of convolutional neural network (CNN) features for MEF.
Hui Li 0029, Lei Zhang 0006
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Feature Fusion for Scene Text Detection

2018 13th IAPR International Workshop on Document Analysis Systems (DAS), 2018
A significant challenge in scene text detection is the large variation in text sizes. In particular, small text are usually hard to detect. This paper presents an accurate oriented text detector based on Faster R-CNN. We observe that Faster R-CNN is suitable for general object detection but inadequate for scene text detection due to the large variation
Zhen Zhu 0006, Minghui Liao, Baoguang Shi, Xiang Bai   +3 more
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Feature Comparison and Feature Fusion for Traditional Dances Recognition

2013
Traditional dances constitute a significant part of the cultural heritage around the world. The great variety of traditional dances along with the complexity of some dances increases the difficulty of identifying such dances, thus making the traditional dance recognition a challenging subset within the general field of activity recognition.
Ioannis Kapsouras, Stylianos Karanikolos, Nikolaos Nikolaidis 0001, Anastasios Tefas   +3 more
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A method towards biometric feature fusion

International Journal of Biometrics, 2009
For multimodal biometric person recognition, information fusion can be classified into several levels: rank, decision, sensor, feature and match-score levels. In this paper, a novel method is proposed to fuse information from two or more biometric sources at feature fusion level.
Lin Huang 0001, Hanqi Zhuang, Salvatore D. Morgera   +2 more
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Linear dependency modeling for feature fusion

2011 International Conference on Computer Vision, 2011
This paper addresses the independent assumption issue in fusion process. In the last decade, dependency modeling techniques were developed under a specific distribution of classifiers. This paper proposes a new framework to model the dependency between features without any assumption on feature/classifier distribution.
Andy Jinhua Ma, Pong Chi Yuen
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Hierarchical Feature Fusion for Visual Tracking

2007 IEEE International Conference on Image Processing, 2007
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from cluttered scenes. The tracked object is described by several models of different complexity, which are probabilistically linked together.
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavros J. Perantonis, Sergios Theodoridis   +3 more
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