Results 111 to 120 of about 12,832 (282)
Adversarial Attack and Defense: A Survey
In recent years, artificial intelligence technology represented by deep learning has achieved remarkable results in image recognition, semantic analysis, natural language processing and other fields.
Hongshuo Liang +4 more
core +1 more source
Abstract Local religious traditions serve as informal environmental institutions, characterized by socially embedded norms that guide behaviour without formal enforcement and influence human–environment interactions. This study investigates the role of Bonbibi worship as a system of moral regulation in the Bangladeshi Sundarbans and examines the ...
Mohammad Raqibul Hasan Siddique +1 more
wiley +1 more source
Llm-ga: A gradient-based multi-label adversarial attack by large language models
Deep neural networks (DNNs) are highly sensitive to small, meticulously crafted perturbations, which have been utilized in adversarial attacks, threatening the reliability of DNNs in practical applications. Current adversarial attack methods rely heavily
Yujiang Liu +4 more
doaj +1 more source
With the development of artificial intelligence, machine learning algorithms and deep learning algorithms are widely applied to attack detection models. Adversarial attacks against artificial intelligence models become inevitable problems when there is a
Yong Fang +3 more
doaj +1 more source
Artificial intelligence (AI) offers transformative potential for paediatric diagnosis and treatment, yet implementation faces unique challenges, including data scarcity, algorithmic bias, and children's developmental physiology. This review examines current applications and charts a path toward transparent, equitable, and trustworthy AI in child health.
Ruisong Wang +3 more
wiley +1 more source
DIPA: Adversarial Attack on DNNs by Dropping Information and Pixel-Level Attack on Attention
Deep neural networks (DNNs) have shown remarkable performance across a wide range of fields, including image recognition, natural language processing, and speech processing. However, recent studies indicate that DNNs are highly vulnerable to well-crafted
Jing Liu +4 more
doaj +1 more source
Using art history to explore society's changing connections with agriculture
Food insecurity is a looming challenge that especially affects those least fortunate. Consumer food choices have a substantial impact on the sustainability of current food systems. Here, we use art as a lens through which to consider our contemporary and historical relationship to one of the world's most crucial crops, the potato, in the context of the
Edward F. Hill‐King +2 more
wiley +1 more source
Researching infrared adversarial attacks is crucial for ensuring the safe deployment of security-sensitive systems reliant on infrared object detectors.
Zhiyang Hu +6 more
doaj +1 more source
A Smart Adversarial Attack on Deep Hashing Based Image Retrieval
Deep hashing based retrieval models have been widely used in large-scale image retrieval systems. Recently, there has been a surging interest in studying the adversarial attack problem in deep hashing based retrieval models. However, the effectiveness of
Yi Wang +11 more
core +1 more source
Stop Using Limiting Stimuli as a Measure of Sensitivities of Energetic Materials
ABSTRACT Accurately estimating the sensitivity of explosive materials is a potentially life‐saving task that requires standardised protocols across nations. One of the most widely applied procedures worldwide is the so‐called ‘1‐In‐6’ test from the United Nations (UN) Manual of Tests in Criteria, which estimates a ‘limiting stimulus’ for a material. In
Dennis Christensen, Geir Petter Novik
wiley +1 more source

