132 citations · 196 across the 20 of their papers we have counts for
9 papers · 1 filter
Detecting and Correcting Adversarial Images Using Image Processing Operations
Huy H. Nguyen, Minoru Kuribayashi, Junichi Yamagishi +1
Deep neural networks (DNNs) have achieved excellent performance on several tasks and have been widely applied in both academia and industry. However, DNNs are vulnerable to adversa…
A Method for Identifying Origin of Digital Images Using a Convolution Neural Network
Rong Huang, Fuming Fang, Huy H. Nguyen +2
The rapid development of deep learning techniques has created new challenges in identifying the origin of digital images because generative adversarial networks and variational aut…
Security of Facial Forensics Models Against Adversarial Attacks
Rong Huang, Fuming Fang, Huy H. Nguyen +2
Deep neural networks (DNNs) have been used in digital forensics to identify fake facial images. We investigated several DNN-based forgery forensics models (FFMs) to examine whether…
Use of a Capsule Network to Detect Fake Images and Videos
Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
The revolution in computer hardware, especially in graphics processing units and tensor processing units, has enabled significant advances in computer graphics and artificial intel…
Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detection
David Ifeoluwa Adelani, Haotian Mai, Fuming Fang +3
Advanced neural language models (NLMs) are widely used in sequence generation tasks because they are able to produce fluent and meaningful sentences. They can also be used to gener…
Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
Huy H. Nguyen, Fuming Fang, Junichi Yamagishi +1
Detecting manipulated images and videos is an important topic in digital media forensics. Most detection methods use binary classification to determine the probability of a query b…