Results 111 to 120 of about 26,076 (260)

Deep Convolutional Generative Adversarial Networks in Image-Based Android Malware Detection

Computers
The recent advancements in generative adversarial networks have showcased their remarkable ability to create images that are indistinguishable from real ones.
Francesco Mercaldo, Fabio Martinelli, Antonella Santone   +2 more
doaj   +1 more source

Ag/Ag2S Nanoparticle‐Based In‐Materio Lightweight Cryptographic System for IoT Edge Security

Advanced Intelligent Systems, EarlyView.
This work presents a nanomaterial‐based in materio encryption method that directly transforms analog signals through nonlinear Ag/Ag2S nanoparticle networks. By exploiting the inherently nonuniform characteristics that arise from random arrangement of nanoparticles as a unique security key, the approach produces highly complex encrypted waveforms ...
Hiroki Tabata, Yuma Yamashita, Yusuke Nakaoka, Oradee Srikimkaew, Muzhen Xu, Yuki Usami, Shunsuke Araki, Hirofumi Tanaka   +7 more
wiley   +1 more source

Epistemic Generative Adversarial Networks

CoRR
Generative models, particularly Generative Adversarial Networks (GANs), often suffer from a lack of output diversity, frequently generating similar samples rather than a wide range of variations. This paper introduces a novel generalization of the GAN loss function based on Dempster-Shafer theory of evidence, applied to both the generator and ...
Muhammad Mubashar, Fabio Cuzzolin
openaire   +2 more sources

Xstainer: A Novel Virtual Staining Tool Powered by Advanced Deep Learning Techniques

Advanced Intelligent Systems, EarlyView.
Xstainer is a deep learning–based virtual staining framework that converts hematoxylin and eosin‐stained whole slide images into multiple histochemical stains, including Masson's trichrome, Periodic acid‐Schiff, Jones methenamine silver, and Toluidine blue.
Fatma Nur Kinali, Derya Demir, Kutsev B. Ozyoruk, Yasin Almalioglu, Emre C. Kose, Drew F. K. Williamson, Gurdeniz Serin, G. Evren Keles, Banu S. Kumbaraci, Ceren Utku, Uguray P. Hacisalihoglu, Ilknur Turkmen, Figen Ozturk, Kayhan Basak, Yavuz Nuri Ertas, Mehmet Turan   +15 more
wiley   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

Advanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

An Intelligent Microfluidics Enabled by Data‐Driven Deep Learning‐Based Microrobot‐Assisted Flow Manipulation

Advanced Intelligent Systems, EarlyView.
An AI‐enabled micromixing framework is developed by integrating cGAN with Bayesian optimization for predictive control of microrobot‐driven flow manipulation. Through this framework, the spatiotemporal evolution of micromixing is learned directly from experimental images, while rapid identification of optimized microrobot actuation strategies is ...
Dineshkumar Loganathan, Chia‐Yuan Chen
wiley   +1 more source

Hamiltonian quantum generative adversarial networks

Physical Review Research
We propose Hamiltonian quantum generative adversarial networks (HQuGANs) to learn to generate unknown input quantum states using two competing quantum optimal controls. The game-theoretic framework of the algorithm is inspired by the success of classical
Leeseok Kim, Seth Lloyd, Milad Marvian
doaj   +1 more source

Transformative skeletal motion analysis: optimization of exercise training and injury prevention through graph neural networks

Frontiers in Neuroscience
IntroductionExercise is pivotal for maintaining physical health in contemporary society. However, improper postures and movements during exercise can result in sports injuries, underscoring the significance of skeletal motion analysis. This research aims
Jiaju Zhu, Zijun Ye, Meixue Ren, Guodong Ma, Guodong Ma   +4 more
doaj   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source

Advancing student outcome predictions through generative adversarial networks

Computers and Education: Artificial Intelligence
Predicting student outcomes is essential in educational analytics for creating personalised learning experiences. The effectiveness of these predictive models relies on having access to sufficient and accurate data. However, privacy concerns and the lack
Helia Farhood, Ibrahim Joudah, Amin Beheshti, Samuel Muller   +3 more
doaj   +1 more source