نتایج جستجو برای: spatial feature

تعداد نتایج: 580259  

Journal: :environmental resources research 0
hamidreza kamyab gorgan university of agricultural sciences and natural resources abdolrassoul salman mahiny associate professor, faculty of fisheries and environmental sciences, gorgan university of agricultural science & natural resource mohammad shahraini assistant professor, engineering & technological collage, golestan university

in this paper, landscape allocation using genetic algorithm (laga), a spatial multi-objective land use optimization software is introduced. the software helps in searching for optimal land use when multiple objectives such as suitability, area, cohesion and edge density indices are simultaneously involved. laga is a flexible and easy to use genetic algorithm-based software for optimizing the sp...

2016
Che Chang Yu Xiaoyang Yu Guang

The traditional image retrieval method is based on single feature retrieval method like color, texture, shape or multi feature weighted fusion method. The retrieval rate of existing methods is not high. This paper presents fusion multi feature image retrieval. Two kinds of feature play a complementary effect in retrieval. Most color feature can not reflect the spatial information of image. Text...

2016
Xiaobing Han Yanfei Zhong Liangpei Zhang

Current hyperspectral remote sensing imagery spatial-spectral classification methods mainly consider concatenating the spectral information vectors and spatial information vectors together. However, the combined spatial-spectral information vectors may cause information loss and concatenation deficiency for the classification task. To efficiently represent the spatial-spectral feature informati...

In this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fMRI) data. In the preprocessing step, the number of fMRI time points is reduced using principal component analysis (PCA). Then, independent component analysis (ICA) is used for further data analysis. It estimates independent components (ICs) of...

Journal: :CoRR 2017
Zhengyang Wang Hao Yuan Shuiwang Ji

The key idea of variational auto-encoders (VAEs) resembles that of traditional auto-encoder models in which spatial information is supposed to be explicitly encoded in the latent space. However, the latent variables in VAEs are vectors, which are commonly interpreted as multiple feature maps of size 1x1. Such representations can only convey spatial information implicitly when coupled with power...

2012
Zifeng Wu Yongzhen Huang Liang Wang Tieniu Tan

The original bag-of-words (BoW) model in terms of image classification treats each local feature independently, and thus ignores the spatial relationships between a feature and its neighboring features, namely, the feature’s context. However, our intuition and empirical studies tell the importance of such spatial information. Although the global spatial information can be captured with the spat...

Journal: :Vision Research 2009
Benjamin Y. Hayden Jack L. Gallant

Attention is thought to be controlled by a specialized fronto-parietal network that modulates the responses of neurons in sensory and association cortex. However, the principles by which this network affects the responses of these sensory and association neurons remains unknown. In particular, it remains unclear whether different forms of attention, such as spatial and feature-based attention, ...

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