In this paper, we conduct a comprehensive study on image style transfer techniques. Firstly, we analyze and classify the existing algorithms of the current style transfer algorithms, and then elaborate on their applications in different fields. In addition, we also summarize the future development ...
like.AdvancedDeepLearningwithKerasisacomprehensiveguidetotheadvanceddeeplearningtechniquesavailabletoday,soyoucancreateyourowncutting-edgeAI.UsingKerasasanopen-sourcedeeplearninglibrary,you'llfindhands-onprojectsthroughoutthatshowyouhowtocreatemoreeffectiveAIwiththelatesttechniques.ThejourneybeginswithanoverviewofMLPs,...
Our Deep Learning-based model is built to detect Audio Deep fakes produced using imitation and synthesis techniques. According to the findings of our ... M Mateen,NZ Bawany - 《Numl International Journal of Engineering & Computing》 被引量: 0发表: 2023年 Ensemble Techniques for Robust Fake ...
Deepfake detection for preventing Audio and Video frauds using Advanced Deep Learning Techniques Deepfake detection for preventing Audio and Video frauds using Advanced Deep Learning Techniquesdoi:10.1109/ICIICS59993.2023.10421486 R Bharadwaj,S Ratnaparkhi,R Rajpurohit,... - International Conference on ...
The main contribution of this research is the development of a forecasting model, named CNN-LSTM, utilizing advanced deep learning techniques for the short-term prediction of natural gas price and movement. The proposed model is based on of two main components. ...
Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on...
By the end of the course, you'll have practical experience with advanced deep learning techniques to advance your career as a data scientist, including evaluating your models on new data using multiple metrics. For Business Training 2 or more people?Get your team access to the full DataCa...
to recent promising SR approaches using GANs (e.g., SRGAN). In general, the family of SR algorithms using deep learning techniques differs from each other in the following major aspects: different types ofnetwork architectures, different types of loss functions, different types of learning principl...
Such advances have benefited greatly by adapting deep learning techniques from computer vision producing novel solutions to a variety of CPath problems, including nucleus instance segmentation1, pathology image quality analysis2 and WSI-level prediction3,4. Although many algorithms have been developed ...
Machine Learning is used to enable robots to learn from their experiences and improve their performance over time. Deep Learning is used to solve specific problems that are difficult to solve with traditional Machine Learning techniques, such as image and speech recognition. By combining these ...