Deep Learning Intensive

Machine Learning, Natural Language Processing, Computer Vision, Adversarial Learning, Neural Networks, NLP

Learn about Complete Life Cycle of a Deep Learning Project. Implement different Neural networks using Tensorflow & Keras

Learn about Complete Life Cycle of a Deep Learning Project. Implement different Neural networks using Tensorflow & Keras

This reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.

Accelerate deep learning and other number-intensive tasks with JAX, Google's awesome high-performance numerical computing library.