Results 121 to 130 of about 96,849 (322)

Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods [PDF]

, 2019
Arif Siddiqi
openalex   +1 more source

Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks [PDF]

, 2020
Taro Kiritani, Koji Ono
openalex   +1 more source

Adversarial Attacks on Hyperbolic Networks

As hyperbolic deep learning grows in popularity, so does the need for adversarial robustness in the context of such a non-Euclidean geometry. To this end, this paper proposes hyperbolic alternatives to the commonly used FGM and PGD adversarial attacks.
Max van Spengler, Jan Zahálka, Pascal Mettes   +2 more
openaire   +2 more sources

Why do we burn? Examining arguments underpinning the use of prescribed burning to manage wildfire risk

People and Nature, EarlyView.
Abstract Managing wildfire risk requires consideration of complex and uncertain scientific evidence as well as trade‐offs between different values and goals. Conflicting perspectives on what values and goals are most important, what ought to be done and what trade‐offs are acceptable complicate those decisions.
Pele J. Cannon, Sarah Clement
wiley   +1 more source

DLSF:A Textual Adversarial Attack Method Based on Dual-level Semantic Filtering [PDF]

Jisuanji kexue
In the field of commercial applications,deep learning-based text models play a crucial role but are also susceptible to adversarial samples,such as the incorporation of confusing vocabulary into reviews leading to erroneous model responses.A strong ...
XIONG Xi, DING Guangzheng, WANG Juan, ZHANG Shuai
doaj   +1 more source

Transferable Sparse Adversarial Attack [PDF]

, 2021
Ziwen He, Wei Wang, Jing Dong, Tieniu Tan   +3 more
openalex   +1 more source

The transformative potential of artificial intelligence in pediatric medicine: Current applications, methodological challenges, and future directions

Pediatric Investigation, EarlyView.
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, Xiaoman Ding, Wanyue Zhang, Tieliu Shi   +3 more
wiley   +1 more source

Stop Using Limiting Stimuli as a Measure of Sensitivities of Energetic Materials

Propellants, Explosives, Pyrotechnics, EarlyView.
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

Integrating multimodal data and machine learning for entrepreneurship research

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source

Adversarial Attack and Defense in Breast Cancer Deep Learning Systems. [PDF]

Bioengineering (Basel), 2023
Li Y, Liu S.
europepmc   +1 more source