Adversarial training - Open Access .click

Results 161 to 170 of about 217,331 (267)

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu +8 more
wiley +1 more source

Adversarial training for prostate cancer classification using magnetic resonance imaging. [PDF]

Quant Imaging Med Surg, 2022
Hu L +5 more
europepmc +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu +4 more
wiley +1 more source

Robust Deep Active Learning via Distance-Measured Data Mixing and Adversarial Training. [PDF]

Entropy (Basel)
Song S, Wang X, Dong S, Jiang J.
europepmc +1 more source

Sustainable Live Sound Monitoring and Classification System Enabled by a Triboelectric Nanogenerator and Machine Learning Techniques

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A high‐performance Triboelectric Nanogenerator (TENG) acoustic sensor using polyimine/graphite polypropylene (PI/GP) was developed for real‐time, sustainable sound monitoring and classification. The self‐powered device delivers 25.67 μW output power, 92.7% accuracy with MobileNet V1, and powers a wireless transmission circuit, demonstrating dual ...
Majid Haji Bagheri +8 more
wiley +1 more source

An incremental adversarial training method enables timeliness and rapid new knowledge acquisition. [PDF]

Sci Rep
Ge Y, Dong Y, Sun H, Liu Y, Wang C.
europepmc +1 more source

Log Sequence Anomaly Detection Method Based on Contrastive Adversarial Training and Dual Feature Extraction. [PDF]

Entropy (Basel), 2021
Wang Q, Zhang X, Wang X, Cao Z.
europepmc +1 more source

Computationally Driven Advances in Cu‐CNT On‐Chip Interconnect Materials: From First Principles to Machine Learning

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A multiscale framework integrating electronic, mechanical, and thermal analysis with machine learning to optimize carbon nanotube interconnects. As the component dimensions in integrated circuits shrink to extreme scales, the complexity of interconnect systems is increasing significantly, necessitating an urgent and comprehensive upgrade of ...
Changhong Zhang +11 more
wiley +1 more source

Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images. [PDF]

IEEE Trans Med Imaging, 2021
Gao M, Fessler JA, Chan HP.
europepmc +1 more source

Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie +10 more
wiley +1 more source

adversarial attacks
deep learning
robustness

adversarial robustness
adversarial attack
adversarial examples

data augmentation
deep neural network
adversarial machine learning