Today, we will learn the basic concepts of deep learning and how the technical world is rapidly changing because of the innovations in deep learning. We will discuss the introduction and history of deep learning and how it has evolved with time. After that, we will discuss some important fiel...
In addition, the employment of graphic processing units (GPUs) also renews the interest of researchers in deep learning [46], [47]. With the focus of more attention and efforts, deep learning has burgeoned in recent years and has been applied broadly in industry. For instance, deep belief ...
1.3Deep learning Deep learningis currently one of the hottest areas of research inAI. Models based ondeep learningplay major roles in image recognition, speech recognition,NLP, and many other applications. The vast majority of MRC models nowadays are based ondeep learningas well. Therefore this ...
Deep learning is a subset of machine learning that uses multilayered neural networks, to simulate the complex decision-making power of the human brain.
Interest for deep learning in radiology has increased tremendously in the past decade due to the high achievable performance for various computer vision tasks such as detection, segmentation, classification, monitoring, and prediction. This article provi
Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research ...
Over recent decades, machine learning (ML) has been considered an important innovation with prodigious success in industry1. One key aspect of ML is that it improves itself automatically by uncovering the critical relationship between raw inputs and final outputs from a given dataset. This self-up...
those with no prior machine learning or statistics experience. The book provides concise, well-annotated code examples using TensorFlow with Keras. And with corresponding PyTorch examples provided online, the book covers the two dominating Python libraries used for deep learning in industry and academia...
Additionally, the platform contains toolkits for cutting-edge research, such as Paddle Quantum for models of quantum computing and Paddle Graph Learning for models of graph learning. “That’s why PaddlePaddle is quite popular in China right now. Developers are using such toolkits, not just the ...
Machine learning models need inference engines and good datasets. OpenVINO and Anomalib are open toolkits from Intel that help enterprises set up both.