Results 251 to 260 of about 16,062,156 (297)

Sharing model with multi-level feature representations

2014 IEEE International Conference on Image Processing (ICIP), 2014
Hierarchical classification models have been proposed to achieve high accuracy by transferring effective information across the categories. One important challenge for this paradigm is to design what can be transferred across the categories. In this paper, we propose a novel method to learn a sharing model by taking advantage of multi-level feature ...
Li Shen 0005, Gang Sun 0005, Shuhui Wang, Enhua Wu, Qingming Huang   +4 more
openaire   +1 more source

Multi-level Resolution Features for Classification of Transportation Trajectories

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), 2015
We explore the use of filter-like multi-level resolution features of a positional trajectory for classification. Our approach is time and location agnostic which increases generality. Several filter types are discussed and used in feature extraction including moments and wavelets. Previous work by Bolbol et al. is extended to incorporate these features
Aidan Macdonald, Jeffrey Ellen
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Pyramid multi-level features for facial demographic estimation

Expert Systems with Applications, 2017
The proposed approach can run in real-time applications.The use of specific hierarchical order for demographic estimation.Several public databases are used to assess the advantages of the approach.The advantages of Pyramid Multi-Level face representation. We present a novel learning system for human demographic estimation in which the ethnicity, gender
Salah Eddine Bekhouche, Abdelkrim Ouafi, Fadi Dornaika, Abdelmalik Taleb-Ahmed, Abdenour Hadid   +4 more
openaire   +1 more source

Multi-Level Feature Learning for Pedestrian Attribute Recognition

Proceedings of the 2019 3rd High Performance Computing and Cluster Technologies Conference, 2019
Pedestrian attribute recognition is important for many subjects such as pedestrian tracking and person re-identification in monitoring scenario. Recently plenty of models address this task with deeply learned feature representations, but there still great potentials to make further progress due to some variations including low resolution, occlusion and
Mengling Deng, Jianbiao He
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Brain Tissue Segmentation Integrating Multi-level Features

2019 Seventh International Conference on Advanced Cloud and Big Data (CBD), 2019
Automatic and accurate segmentation of brain tissues from magnetic resonance imaging (MRI) is significantly important in the clinical applications and scientific research. In this paper, we proposed a novel brain tissue segmentation approach integrating multi-level features under the fully convolutional neural network framework.
Fei Wu, Yifei Li, Jian Zhu, Bin Zhou, Youyong Kong, Huazhong Shu   +5 more
openaire   +2 more sources

Learning Multi-Level Features for Breast Mass Detection

Proceedings of the 2nd International Symposium on Image Computing and Digital Medicine, 2018
In order to quickly detect masses from mammography images for the early screening of breast cancer, this paper proposes a breast mass detection improved algorithm based on Faster R-CNN. Firstly, we connect multi- level feature maps (conv-4, conv-5) in ZF model to generated candidate regions in RPN, then use the ROI pool layer to extract the features of
Qinggong Zeng, Huiqin Jiang, Ling Ma 0005   +2 more
openaire   +2 more sources

Predicting salient object via multi-level features

Neurocomputing, 2016
A wide variety of methods have been developed to predict where people look in natural scenes focused on pixel-level image attributes. Most existing methods measure the saliency of a pixel or region based on its contrast within a local context or the entire image.
Mingqiang Lin, Chenbin Zhang, Zonghai Chen   +2 more
openaire   +2 more sources

Multi-level Feature Combination in Dialogue State Tracking

2019
Dialogue State Tracking is one of the most important component in task-oriented dialog system, which can update the dialogue state and accurately estimate the compact state representation. This paper introduces a multi-level feature combination to capture correlation on the basis of the entire dialog and slots.
Yang Zheng, Ruifang Liu, Sheng Gao
openaire   +2 more sources

Multi-level feature driven storage management of surveillance videos

Pervasive and Mobile Computing, 2021
Abstract Surveillance videos in smart environments have become commodities nowadays, which enable many novel applications, including various video analytics that turn videos into semantic results. In addition to live feeds, surveillance videos may be saved in a storage server for on-demand user-defined queries in the future.
Min-Han Tsai, Nalini Venkatasubramanian, Cheng-Hsin Hsu   +2 more
openaire   +1 more source

A Multi-Level Freeform Surface Feature Model

Volume 2: 27th Computers and Information in Engineering Conference, Parts A and B, 2007
Feature modelling is a valuable technology to define and manipulate product models through advanced operations. Parameters and constraints can be included in feature models to represent particular design intent. In this way, entire families of shapes, not just specific instances, can be modelled.
Paulos J. Nyirenda, Willem F. Bronsvoort
openaire   +1 more source