Deep learningDBNAcceleration strategyData skewRDD cacheIn recent years, image processing especially for remote sensing technology has developed rapidly. In the field of remote sensing, the efficiency of processing remote sensing images has been a...doi:10.1186/s13638-018-1255-6Ying, ChangtianHuang, ZhenYing, ChangyanHind...
In this paper, we propose a novel deep learning based network compression algorithm to compress the heavily-designed DNN to a small one. Further, we develop a deep learning-driven mobile application for herb image recognition, which can run entirely on a single smartphone. The application runs ...
Deep-learning-based tomographic imaging is an important application of artificial intelligence and a new frontier of machine learning. Deep learning has been widely used in computer vision and image analysis, which deal with existing images, improve thes
Due to their self-learning and generalization ability over large amounts of data, deep learning recently has also gained great interest in multi-modal medical image segmentation. In this paper, we give an overview of deep learning-based approaches for multi-modal medical image segmentation task. ...
I stumbled upon the above tweet by Leon Palafox, a Postdoctoral Fellow at theThe University of Arizona Lunar and Planetary Laboratory, and reached out to him to discuss his success with GPUs and share it with other developers interested in usingdeep learningfor image processing. ...
Image Processing Toolbox Deep Learning for Image Processing Neural Style Transfer Using Deep Learning On this page Load Data Load Feature Extraction Network Preprocess Data Initialize Transfer Image Define Loss Functions and Style Transfer Parameters Specify Training Options Train the Network Postprocess ...
artificial intelligence; deep learning; reinforcement learning; image processing1. Introduction Images constitute one of the most important forms of communication used by society and contain a large amount of important information. The human vision system is usually the first form of contact with media...
For instance, you may implement a machine learning algorithm that can distinguish pictures of dogs from pictures of cats. Initially, the algorithm may not be very good at it. But as you train the algorithm by giving it examples of cats and dogs, it will learn to distinguish them. Since ...
Deep learning is a complex machine learning algorithm that involves learning inherent rules and representation levels of sample data through large neural networks with multiple layers. It is popular for its automatic feature extraction capabilities and is applied in various areas such as CNN, LSTM, RN...
Razzak, M.I., Naz, S., Zaib, A. (2018). Deep Learning for Medical Image Processing: Overview, Challenges and the Future. In: Dey, N., Ashour, A., Borra, S. (eds) Classification in BioApps. Lecture Notes in Computational Vision and Biomechanics, vol 26. Springer, Cham. https://...