Support Vector Machine and Spiking Neural Networks for Data Driven prediction of crowd character movement

Tabarez-Paz, Israel; Rudomín, Isaac; Prez, Hugo

doi:10.7551/978-0-262-33936-0-ch102

Cited by 1 publication

(1 citation statement)

References 21 publications

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“…Zooming our considerations out from a particular vehicle or agent, Prez et al [91] utilized the SVM and SNN as two alternatives for predicting crowd movement trajectory, which is critical for many physical safety applications. They simulated crowd movement at the microscopic level (interaction between individual agents).…”

Section: Trustworthy and Explainable Snnsmentioning

confidence: 99%

Trustworthy Artificial Intelligence Methods for Users’ Physical and Environmental Security: A Comprehensive Review

Szymoniak,

Depta,

Karbowiak

et al. 2023

Applied Sciences

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Artificial Intelligence is an indispensable element of the modern world, constantly evolving and contributing to the emergence of new technologies. We meet it in everyday applications, primarily using intelligent systems that aim to improve our lives. Artificial Intelligence techniques must inspire users’ trust because they significantly impact virtually every industry and person. For this reason, systems using Artificial Intelligence are subject to many requirements to verify their trustworthiness in various aspects. This review focused on users’ physical and environmental security, considering the safety and robustness dimensions of Trustworthy Artificial Intelligence. We examined these Trustworthy Artificial Intelligence solutions and dimensions because security is one of the most-critical aspects of human life and can be considered in many different contexts. We examined the trustworthiness of Artificial Intelligence techniques in systems supporting road safety and securing computer network users. Also, we analyzed the challenges and requirements of the newly designed solutions using Trustworthy Artificial Intelligence methods. Verifying Trustworthy Artificial Intelligence solutions and their practical use will increase users’ physical and environmental security.

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Section: Trustworthy and Explainable Snnsmentioning

confidence: 99%