Artificial Immune System of Secure Face Recognition Against Adversarial Attacks

Fuente: arXiv
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Auteurs principaux: Ren, Min, Wang, Yunlong, Zhu, Yuhao, Huang, Yongzhen, Sun, Zhenan, Li, Qi, Tan, Tieniu
Format: Preprint
Publié: 2024
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author Ren, Min
Wang, Yunlong
Zhu, Yuhao
Huang, Yongzhen
Sun, Zhenan
Li, Qi
Tan, Tieniu
author_facet Ren, Min
Wang, Yunlong
Zhu, Yuhao
Huang, Yongzhen
Sun, Zhenan
Li, Qi
Tan, Tieniu
contents Insect production for food and feed presents a promising supplement to ensure food safety and address the adverse impacts of agriculture on climate and environment in the future. However, optimisation is required for insect production to realise its full potential. This can be by targeted improvement of traits of interest through selective breeding, an approach which has so far been underexplored and underutilised in insect farming. Here we present a comprehensive review of the selective breeding framework in the context of insect production. We systematically evaluate adjustments of selective breeding techniques to the realm of insects and highlight the essential components integral to the breeding process. The discussion covers every step of a conventional breeding scheme, such as formulation of breeding objectives, phenotyping, estimation of genetic parameters and breeding values, selection of appropriate breeding strategies, and mitigation of issues associated with genetic diversity depletion and inbreeding. This review combines knowledge from diverse disciplines, bridging the gap between animal breeding, quantitative genetics, evolutionary biology, and entomology, offering an integrated view of the insect breeding research area and uniting knowledge which has previously remained scattered across diverse fields of expertise.
format Preprint
id arxiv_https___arxiv_org_abs_2406_18144
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Artificial Immune System of Secure Face Recognition Against Adversarial Attacks
Ren, Min
Wang, Yunlong
Zhu, Yuhao
Huang, Yongzhen
Sun, Zhenan
Li, Qi
Tan, Tieniu
Computer Vision and Pattern Recognition
Insect production for food and feed presents a promising supplement to ensure food safety and address the adverse impacts of agriculture on climate and environment in the future. However, optimisation is required for insect production to realise its full potential. This can be by targeted improvement of traits of interest through selective breeding, an approach which has so far been underexplored and underutilised in insect farming. Here we present a comprehensive review of the selective breeding framework in the context of insect production. We systematically evaluate adjustments of selective breeding techniques to the realm of insects and highlight the essential components integral to the breeding process. The discussion covers every step of a conventional breeding scheme, such as formulation of breeding objectives, phenotyping, estimation of genetic parameters and breeding values, selection of appropriate breeding strategies, and mitigation of issues associated with genetic diversity depletion and inbreeding. This review combines knowledge from diverse disciplines, bridging the gap between animal breeding, quantitative genetics, evolutionary biology, and entomology, offering an integrated view of the insect breeding research area and uniting knowledge which has previously remained scattered across diverse fields of expertise.
title Artificial Immune System of Secure Face Recognition Against Adversarial Attacks
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2406.18144