Results 101 to 110 of about 85,609 (269)

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

Experimental assessment of аdversarial attacks to the deep neural networks in medical image recognition

Informatika, 2019
This paper addresses the problem of dependence of the success rate of adversarial attacks to the deep neural networks on the biomedical image type and control parameters of generation of adversarial examples.
D. M. Voynov, V. A. Kovalev
doaj  

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

Enhancing Adversarial Defense via Brain Activity Integration Without Adversarial Examples

Sensors
Adversarial attacks on large-scale vision–language foundation models, such as the contrastive language–image pretraining (CLIP) model, can significantly degrade performance across various tasks by generating adversarial examples that are ...
Tasuku Nakajima, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama   +4 more
doaj   +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

CycleGAN-Gradient Penalty for Enhancing Android Adversarial Malware Detection in Gray Box Setting

IEEE Access
Adversarial attacks pose significant threats to Android malware detection by undermining the effectiveness of machine learning-based systems. The rapid increase in Android apps complicates the management of malicious software that can compromise user ...
Fabrice Setephin Atedjio, Jean-Pierre Lienou, Frederica F. Nelson, Sachin S. Shetty, Charles A. Kamhoua   +4 more
doaj   +1 more source

Adversarial Attacks and Defences: A Survey

CoRR, 2018
Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past. In the last few years, deep learning has advanced radically in such a way that it can surpass human-level performance on a number ...
Anirban Chakraborty 0003, Manaar Alam, Vishal Dey, Anupam Chattopadhyay, Debdeep Mukhopadhyay   +4 more
openaire   +2 more sources

Generative AI—the Transgression of Technology

Systems Research and Behavioral Science, EarlyView.
ABSTRACT This article offers a systems‐theoretical analysis of generative artificial intelligence (GenAI) grounded in Niklas Luhmann's sociology of technology. It addresses a central conceptual problem: How GenAI can be understood within a theoretical framework that has traditionally defined technology as a means of stabilising action through causal ...
Jesper Tække
wiley   +1 more source