Research on related technologies of vision target tracking based on discrete differential algorithm for deep learning

Zhang, Changqi; Guan, Yuanyuan

doi:10.3233/jifs-179128

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Three kinds of tracking algorithms based on deep learning: depth-based tracking algorithm based on association filtering, detection-based tracking algorithm and template-based tracking algorithm [ 6 ].…”

Section: Target Tracking Methods Based On Deep Learningmentioning

confidence: 99%

Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence

Wang

2022

Computational Intelligence and Neuroscience

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Target tracking is an important subject in computer vision technology, which has developed rapidly in recent ten years, and its application have become wider and wider. In this process, it has transferred from a simple experimental tracking environment to a complex real scene where more challenges need to be solved. The rapid development of deep learning has promoted the research progress of digital vision. Target tracking technology is an important foundation of digital vision research, which makes it develop from academia to industry. In this paper, a method of target tracking using MDNet is introduced. Starting with the attention mechanism, two attention mechanisms are added to extract and integrate the better features. Case partitioning is used to reduce the investment of tracking module and minimize the network size during tracking, and its result can be prevented from getting worse. Finally, the experiment is analyzed in detail.

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Section: Target Tracking Methods Based On Deep Learningmentioning

confidence: 99%

Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence

Wang

2022

Computational Intelligence and Neuroscience

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“…Based on the neural network model, article [19] proposed a new simulation method of computer network security. In order to promote the development of visual target tracking technology, article [20] uses discrete differential algorithm in computer to assist analysis. Article [21] studied the influence factors of the stability of tailings dam based on multi-source information fusion method.…”

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confidence: 99%

Big data analysis techniques for intelligent systems

Farouk

Dou

2019

IFS

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Recently, Internet of Things (IoT), Cloud, Big Data and AI gained a great attention as the most research topics. They cover not only information and communication technology, but also all kinds of intelligent systems in our society, including business, finance, industry, manufacture, management, and environment. As a result of the extensive use of these new technologies, a huge volume of data in different formats are generated much faster than before. Big data, characterized by high volume, variety and velocity, increasingly drives decision making and is changing the landscape of intelligent systems, from governments, organizations, communities to individual decision making. Cognitive big data analytics that discovers insights from pieces of evidence has a high demand for computing efficiency, knowledge discovery, problem-solving, and event prediction/prescription. It also poses great challenges in terms of data, process, analytical modelling and management for organizations to turn big data into big insight. Due to the increase in data size, complexity, and formats, it is no longer practical to anticipate and model all possible interactions and data processing in big data-based intelligent systems using the

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Research on related technologies of vision target tracking based on discrete differential algorithm for deep learning

Cited by 2 publications

References 23 publications

Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence

Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence

Big data analysis techniques for intelligent systems

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