Calibration of AOTF-based 3D measurement system using multiplane model based on phase fringe and BP neural network

Zhao, Haitao; Shi, Shaoguang; Jiang, Hongzhi; Zhang, Ying; Xu, Zefu

doi:10.1364/oe.25.010413

Cited by 23 publications

(10 citation statements)

References 21 publications

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“…In the 1980s, a California Institute of Technology professor proposed a single-mode network model and called it the Hopfield network model [ 11 ]. It is mainly used in voltage testing and has a significant guarantee for voltage safety performance.…”

Section: Psychological Pressure Recognition Methods Of Mobile Human-c...mentioning

confidence: 99%

Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment

Zhang

2022

Applied Bionics and Biomechanics

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Since the 1980s, the research of artificial neural networks in the field of artificial intelligence has become more and more common. It accepts nonlinear parallel processing, has strong learning and flexibility, and can be used for influencing factor analysis. The ideal power values and triggers are obtained in the Hopfield network model using genetic algorithm, which best avoids the drawbacks of the Hopfield network model instillation learning method. Through the BP of mobile human-computer interaction equipment, hereditary, genetic algorithms, and Hi-PLS regression method in the artificial neural network, the psychological pressure of college students is identified, evaluated, and predicted from three dimensions such as learning, life, and personal events. This makes it possible to understand the current physical and mental conditions of the students in a timely manner, guide to relieve anxiety and fear, and reach a safe psychological level. The three test results are less than 1%, which has high research significance and value.

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Section: Psychological Pressure Recognition Methods Of Mobile Human-c...mentioning

confidence: 99%

Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment

Zhang

2022

Applied Bionics and Biomechanics

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“…The exercise of new model is in view of the principle of gradient descent, and the threshold attributes of gravity are constantly revised to avoid falling into local minimum attributes. GA can realize global search [20]. Through global search, the gravity and threshold of new model could either be redetermined without impacting the nodes, implicit layers, and other specifications of new model [21].…”

Section: Bp Neural Networkmentioning

confidence: 99%

Application of Optimized BP Neural Network In Financial Alert System

Qiaoyi

2022

Journal of Function Spaces

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The development of economic globalization not only brings development opportunities for enterprise development but also causes the rapid changes of economic environment. Global enterprises are facing many development challenges. It is very significant to implement financial alert. However, most of the existing financial alert systems are based on traditional quantitative analysis and cannot face the demand of big data growth. Based on this, main body of a book studies and analyzes the request of optimized BP neural network in financial alert system. Based on the financial early warning and a brief analysis of the development requirements of BP neural network, this paper establishes a financial early warning model for BP neural network. Considering the shortcomings of BP neural network, genetic algorithm is used to optimize the specification. Finally, a new reference scheme is provided for economic early warning. And use the following steps to create a list, taking into account the volume analysis in the conceptual design. The emulation results indicates that the optimized BP neural network can accelerate the convergence, has strong stability, and has higher accuracy in financial alert.

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“…Most of the existing abstraction generation models of images are based on the encoder-decoder architecture. The encoder encodes the image to obtain visual features, and the decoder decodes the visual features to generate sentences, thus completing the multi-mode conversion from image to text [6]. This paper makes full use of multi-modal information, extracts image features and text features at the same time in the encoding process, and fuses multi-modal features in the decoding process to model the abstract.…”

Section: Methods Of Generating a Chinese Abstract Of Images Based On Mmentioning

confidence: 99%

“…x 5 k ∈ R M 5 ×M 5 represents the K-th group features of the conv5-3 output of the group 5 module convolution layer, and Formula (1) represents group k feature mapping x 6 k of the group 6 module convolution layer [11]:…”

Section: Visual Feature Extraction Network Of the Single Labelmentioning

confidence: 99%

Feature Input Symmetry Algorithm of Multi-Modal Natural Language Library Based on BP Neural Network

Lin

2019

Symmetry

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When using traditional knowledge retrieval algorithms to analyze whether the feature input of words in multi-modal natural language library is symmetrical, the symmetry of words cannot be analyzed, resulting in inaccurate analysis results. A feature input symmetric algorithm of multi-modal natural language library based on BP (back propagation) neural network is proposed in this paper. A Chinese abstract generation method based on multi-modal neural network is used to extract Chinese abstracts from images in multi-modal natural language library. The Word Sense Disambiguation (WSD) Model is constructed by the BP neural network. After the word or text disambiguation is performed on the Chinese abstract in the multi-modal natural language library, the feature input symmetry problem in the multi-modal natural language library is analyzed according to the sentence similarity. The experimental results show that the proposed algorithm can effectively analyze the eigenvalue symmetry problem of the multi-modal natural language library. The maximum error rate of the analysis algorithm is 7%, the growth rate of the analysis speed is up to 50%, and the average analysis time is 540.56 s. It has the advantages of small error and high efficiency.

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Calibration of AOTF-based 3D measurement system using multiplane model based on phase fringe and BP neural network

Cited by 23 publications

References 21 publications

Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment

Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment

Application of Optimized BP Neural Network In Financial Alert System

Feature Input Symmetry Algorithm of Multi-Modal Natural Language Library Based on BP Neural Network

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