1. Introduction to Generative AI and Deepfake Technology 2. Deepfake Detection Principles and Challenges 3. Ethical Considerations with the Use of Deepfakes 4. Setting Up yourMachinefor Deepfake Detection using Python 5. Deepfake Datasets 6. Techniques for Deepfake Detection 7. Detection of Deepfake Images 8. Detection of Deepfake Video ...
generate'fake data'or'fake images'.This study was carried out using Python and its libraries.We used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were real.Ten seconds were allotted for each video.There were 318 ...
Kandasamy V, Hubálovskỳ Š, Trojovskỳ P (2022) Deep fake detection using a sparse auto encoder with a graph capsule dual graph CNN. PeerJ Comput Sci 8:953. https://doi.org/10.7717/peerj-cs.953 Article Google Scholar Haliassos A, Vougioukas K, Petridis S, Pantic M (2021...
Python dessa-oss/fake-voice-detection Star372 Using temporal convolution to detect Audio Deepfakes machine-learningdeep-learningfake-newsdeep-learning-tutorialmachine-learning-tutorialsdeep-fakes UpdatedNov 21, 2022 Python This telegram bot uses the first order model to produce deepfakes video notes ...
(2024) [49] used ResNet-Swish-BiLSTM to classify consecutive video frames as real or fake. Previous works have shown that using multiple modalities and feature fusion instead of a single type of input can improve the performance of Deepfake detection. This allows the model to construct a ...
ResN et-50 has been used in deepfake detection by training the network on a large dataset of real and fake videos In this paper, Resnet50 and LSTM [13] are combined to make a hybrid architecture are used in deep fake video detection as a web framework using python. Combining ResNet50...
Use KerasCV, Python, Tensorflow, PyTorch, & JAX for Image Recognition, Object Detection, and Stable Diffusion All levels 42 Lectures 6h48m $29.99 $199.99 85% OFF! 4.8 Generative AI Data Science: Transformers for Natural Language Processing ChatGPT, GPT-4, BERT, Deep Learning, Machine Learni...
fake_loss = loss_fn(discriminator(fake_images), 0) discriminator_loss = real_loss + fake_loss optimizer_d.zero_grad() discriminator_loss.backward() optimizer_d.step() # 训练生成器 fake_images = generator(real_images) generator_loss = loss_fn(discriminator(fake_images), 1) ...
Fake news detection using deep learning Final master thesis projectThis repository is focused on finding fake news using deep learningThere are multiple methods focused on achieving this goal, but the objective of this work is discriminating the fake ones by only looking at the text. No graphs, ...
The new deepfake detection vision model is an ensemble deep learning model that is trained on the best parameters and can classify images as either real (0) or fake (1), along with providing a probability score to indicate the confidence level of the prediction. The application is designed ...