Adversarial path planning for optimal CCTV surveillance: a case study on nuclear facility security optimization. [PDF]
Sci RepSalman AE, Shaaban N, Zidan WI, Saad MH.
europepmc +1 more source
Latent Transfer Attack: Adversarial Examples via Generative Latent Spaces [PDF]
Eitan Shaar +4 more
openalex
Environmental Policy and Governance, EarlyView.ABSTRACT Despite South Korea's extensive forest coverage, which accounts for approximately 63% of its total land area, the country imports over 83% of its timber needs and has shown a gradual decline in forest carbon sequestration capacity. The Circular Forest Management Policy (CFMP) addresses these challenges through systematic forest resource ...
Seoryeon Son +4 more
wiley +1 more source
Toward Adversarial Robustness Network Intrusion Detection Based on Multi-Model Ensemble Approach. [PDF]
Sensors (Basel)Le TT, Cho J, Shin D, Kim H.
europepmc +1 more source
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples [PDF]
, 2019 Chang Xiao, Changxi Zheng
openalex +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
A novel hybrid framework integrating GA-driven 3D ResUNetGAN for MRI brain tumor segmentation. [PDF]
PLoS OneKirubakaran M, Mohan J.
europepmc +1 more source
The Migration Analysis of Adversarial Examples with Convolutional Neural Networks. [PDF]
Jin Xing
openalex +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Epilepsia Open, EarlyView.Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Auto-segmentation and dose accuracy evaluation of synthetic computed tomography generated from pelvis cone-beam computed tomography images using a cycle-generative adversarial network with a novel loss function. [PDF]
Phys Imaging Radiat OncolAnbumani S +7 more
europepmc +1 more source