Deepfakes generation and detection: State-of-the-art, open challenges, countermeasures, and way forward
Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …
modern tools such as Tensorflow or Keras, and open-source trained models, along with …
Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …
giving directions of solar energy conversion systems (design, modeling, and operation) …
Deepfakes and beyond: A survey of face manipulation and fake detection
The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …
learning techniques, in particular Generative Adversarial Networks, have led to the …
Hybrid lstm and encoder–decoder architecture for detection of image forgeries
With advanced image journaling tools, one can easily alter the semantic meaning of an
image by exploiting certain manipulation techniques such as copy clone, object splicing …
image by exploiting certain manipulation techniques such as copy clone, object splicing …
Faceforensics: A large-scale video dataset for forgery detection in human faces
With recent advances in computer vision and graphics, it is now possible to generate videos
with extremely realistic synthetic faces, even in real time. Countless applications are …
with extremely realistic synthetic faces, even in real time. Countless applications are …
Face recognition based on convolutional neural network
Face recognition is of great importance to real world applications such as video surveillance,
human machine interaction and security systems. As compared to traditional machine …
human machine interaction and security systems. As compared to traditional machine …
Deepfakes generation and detection: a short survey
Z Akhtar - Journal of Imaging, 2023 - mdpi.com
Advancements in deep learning techniques and the availability of free, large databases
have made it possible, even for non-technical people, to either manipulate or generate …
have made it possible, even for non-technical people, to either manipulate or generate …
Detection and localization of image forgeries using resampling features and deep learning
Resampling is an important signature of manipulated images. In this paper, we propose two
methods to detect and localize image manipulations based on a combination of resampling …
methods to detect and localize image manipulations based on a combination of resampling …
A review of image processing techniques for deepfakes
Deep learning is used to address a wide range of challenging issues including large data
analysis, image processing, object detection, and autonomous control. In the same way …
analysis, image processing, object detection, and autonomous control. In the same way …
Detecting and mitigating adversarial perturbations for robust face recognition
Deep neural network (DNN) architecture based models have high expressive power and
learning capacity. However, they are essentially a black box method since it is not easy to …
learning capacity. However, they are essentially a black box method since it is not easy to …