Results 101 to 110 of about 79,918 (254)

CMDN: Pre-Trained Visual Representations Boost Adversarial Robustness for UAV Tracking

Drones
Visual object tracking is widely adopted to unmanned aerial vehicle (UAV)-related applications, which demand reliable tracking precision and real-time performance.
Ruilong Yu, Zhewei Wu, Qihe Liu, Shijie Zhou, Min Gou, Bingchen Xiang   +5 more
doaj   +1 more source

Adversarial training and deep k-nearest neighbors improves adversarial defense of glaucoma severity detection. [PDF]

Heliyon, 2022
Riza Rizky LM, Suyanto S.
europepmc   +1 more source

A Review of Human–AI Synergy in Smart Energy Management Concepts, Functions, Applications, and Future Frontiers

Energy Internet, EarlyView.
ABSTRACT Smart energy management systems (EMS) are entering a phase of rapid transformation. Artificial intelligence (AI)—including machine learning (ML), deep learning (DL), and reinforcement learning (RL)—has become the computational backbone for real‐time forecasting, scheduling, and control of renewable‐rich power systems.
Sihai An, Jing Qiu, Jiafeng Lin, Zhe Yuan, Weiyi Tian, Zongyu Yao   +5 more
wiley   +1 more source

Review of Artificial Intelligence Adversarial Attack and Defense Technologies

Applied Sciences, 2019
In recent years, artificial intelligence technologies have been widely used in computer vision, natural language processing, automatic driving, and other fields.
Shilin Qiu, Qihe Liu, Shijie Zhou, Chunjiang Wu   +3 more
doaj   +1 more source

Time-Constrained Adversarial Defense in IoT Edge Devices through Kernel Tensor Decomposition and Multi-DNN Scheduling. [PDF]

Sensors (Basel), 2022
Kim M, Joo S.
europepmc   +1 more source

Shape Defense Against Adversarial Attacks

, 2020
Humans rely heavily on shape information to recognize objects. Conversely, convolutional neural networks (CNNs) are biased more towards texture. This is perhaps the main reason why CNNs are vulnerable to adversarial examples. Here, we explore how shape bias can be incorporated into CNNs to improve their robustness. Two algorithms are proposed, based on
openaire   +2 more sources

Looking at quality through a systems lens—Applying systems thinking to the Australian National Disability Insurance Scheme

Australian Journal of Public Administration, EarlyView.
ABSTRACT It is widely recognised that many policy systems are complex, requiring collaboration across different organisations and sectors to address socioeconomic outcomes and inequalities. Yet, the public policy literature is dominated by rational–technical frameworks that struggle to understand complex systems. This paper applies ideas from the field
Jade Hart, Vindhya Weeratunga, Helen Dickinson, Deborah Blackman   +3 more
wiley   +1 more source

Detection and Defense: Student-Teacher Network for Adversarial Robustness

IEEE Access
Defense against adversarial attacks is critical for the reliability and safety of deep neural networks (DNNs). Current state-of-the-art defense methods achieve significant robustness against adversarial attacks.
Kyoungchan Park, Pilsung Kang
doaj   +1 more source

A “Tech First” Approach to Foreign Policy? The Three Meanings of Tech Diplomacy

Global Policy, EarlyView.
ABSTRACT Scholars have recently argued that international politics is plagued by instability as the world rapidly transitions from one crisis to another. This state of “Permacrisis,” or permanent crises between states, is driven by technological innovations which create new kinds of crises and drive competitions between adversarial states.
Ilan Manor
wiley   +1 more source

Adversarial Attacks and Defenses in Fault Detection and Diagnosis: A Comprehensive Benchmark on the Tennessee Eastman Process

IEEE Open Journal of the Industrial Electronics Society
Integrating machine learning into Automated Control Systems (ACS) enhances decision-making in industrial process management. One of the limitations to the widespread adoption of these technologies in industry is the vulnerability of neural networks to ...
Vitaliy Pozdnyakov, Aleksandr Kovalenko, Ilya Makarov, Mikhail Drobyshevskiy, Kirill Lukyanov   +4 more
doaj   +1 more source