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 ...
Visual inspection and medical imaging are two applications that aim to find anything unusual in images. In this course, you’ll train and calibrate specialized models known as anomaly detectors to identify defects. You’ll also use advanced techniques to
Advanced data augmentation techniques expanded the training set: (1) generative adversarial network (GAN); (2) digitally reconstructed radiographs (DRRs) from preoperative hip CT scans. In all, 9063 images, real and generated, were available for training and testing. A deep neural network was ...
Deep learning techniques have shown promise as instruments to improve the precision and effectiveness of mammography-based breast cancer detection. Convolutional neural networks (CNNs) are the most often used models in medical image processing among these methods. By utilizing large datasets, CNNs are...
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. Pré-requisitosIntroduction to Deep Learning with Keras 1 The Keras Functional API...
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...
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 harnessing the power of deep learning techniques, we have developed a custom-designed deep neural network that excels at real-time anomaly detection in video streams. Our innovative solutions, including leveraging the Dlib library and employing effective image processing techniques, have enabled us...
This study presents a novel application of deep learning techniques to investigate the energy absorption-strain relationship in porous metals under varying strain rates. Initially, batch computing is conducted in ABAQUS/Explicit to establish a comprehensive dataset. Subsequently, the microstructure and strai...
techniques, optimizing energy demand forecasts and classifying consumption behavior to enable better resource allocation. The evolution of neural networks introduced deep learning (DL), which used multi-layer architectures to process large datasets, increasing the accuracy of energy load forecasting and ...