Research of Multi Sensor Information Fusion Technology Based on Extension Neural Network

Wang, Tichun; Xie, Yuzhu; Yan, Hao

doi:10.18280/mmep.030303

Cited by 14 publications

(15 citation statements)

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“…The analysis method quantifies the impact of input attributes on the output of the model, ranks the input attributes by the degree of impact, and eliminates those low impact ones. For dimensionality reduction, the NNSA was combined with BP neural network (BPNN) classifier, seeking to quantify the effect of each band on classification accuracy and determine the most impactful band combinations (Wang et al, 2016;Fichera et al, 2017).…”

Section: Data Reduction Based On Annmentioning

confidence: 99%

Hyperspectral Image Recognition Based on Artificial Neural Network

Liang¹,

Liu²,

Wang³

et al. 2018

Neuroquantology

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This paper aims to reduce the dimensions of the data in remote sensing hyperspectral image (HIS), and solve the information redundancy caused by the numerous bands in the image. To this end, the neural network sensitivity analysis (NNSA) was introduced to simplify the dimensionality reduction process. Meanwhile, the convolutional neural network (CNN) was adopted as the classification algorithm for the HIS, seeking to prevent the complex data reconstruction of feature extraction and classification. Then, the proposed method was contrasted with several other classification methods in several experiments. The results show that the proposed method outperformed the contrast plans in classification accuracy. Thus, the artificial neural network (ANN) is good at reducing the dimensions of remote sensing HSI and the CNN is a reliable classification tool. The research findings shed new light on remote sensing image processing and other related operations.

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Section: Data Reduction Based On Annmentioning

confidence: 99%

Hyperspectral Image Recognition Based on Artificial Neural Network

Liang¹,

Liu²,

Wang³

et al. 2018

Neuroquantology

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“…Mass media, as an important medium for information dissemination, influences individuals' health awareness and behaviours through brain cognition. Wang (2016) based on the extension neural network found multi sensor information technology was vital important in information dissemination. Qi and Wang et al (2017) pointed out that production noise interferes with the brain cognition behaviours and is the most harmful to workers.…”

Section: Influence Mechanism Of Brain Cognition On Healthmentioning

confidence: 99%

Influence Mechanism on Health Disparities Based on Brain Cognition, Mass Media and Life Style

Chang¹

2018

Neuroquantology

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Population health status is an important indicator of the economic and social development in a country. Based on the statistics of Chinese General Social Survey (CGSS2015), this paper analyzes the effects of mass media and life style on health through binary logistic regression analysis, and further studies the influence mechanism of brain cognition on health based on the literatures. According to the results of the study, mass media and life style have direct influences on health, and life style plays a mediating role between mass media and health; by contacting healthy information, brain cognition stimulates the consciousness and behaviours of the subjects, which affects the choices of life styles directly and leads to health disparities indirectly. The research conclusions provide practical basis for the development of healthy life styles and improvement of health conditions.

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“…The networks layer is the basic platform to realize the information exchange of the IoV system. According to the multi-network fusion technology [14][15][16], it aims at high data transmission reliability and high-security to guarantee the perceptive data connection is smooth and successful. Based on the networks layer, the data resource layer is in charge of data collection, saving and management from the perception layer.…”

Section: The Classification Of the Iovmentioning

confidence: 99%

The Development of Key Technologies in Applications of Vessels Connected to the Internet

Tian

Liu

et al. 2017

Symmetry

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Abstract:With the development of science and technology, traffic perception, communication, information processing, artificial intelligence and the shipping information system have become important in supporting the realization of intelligent shipping transportation. Against this background, the Internet of Vessels (IoV) is proposed to integrate all these advanced technologies into a platform to meet the requirements of international and regional transportations. The purpose of this paper is to analyze how to benefit from the Internet of Vessels to improve the efficiency and safety of shipping, and promote the development of world transportation. In this paper, the IoV is introduced and its main architectures are outlined. Furthermore, the characteristics of the Internet of Vessels are described. Several important applications that illustrate the interaction of the Internet of Vessels' components are proposed. Due to the development of the Internet of Vessels still being in its primary stage, challenges and prospects are identified and addressed. Finally, the main conclusions are drawn and future research priorities are provided for reference and as professional suggestions for future researchers in this field.

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Research of Multi Sensor Information Fusion Technology Based on Extension Neural Network

Cited by 14 publications

References 0 publications

Hyperspectral Image Recognition Based on Artificial Neural Network

Hyperspectral Image Recognition Based on Artificial Neural Network

Influence Mechanism on Health Disparities Based on Brain Cognition, Mass Media and Life Style

The Development of Key Technologies in Applications of Vessels Connected to the Internet

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