Deep Learning and its Applied Mathematics for Vision Systems used in Industrial Applications Published Special Issues First published:1 January 2022 Last updated:26 May 2024 This issue is now published. Description Today, various machine vision systems are used to monitor the production process and pac...
There are many applications of deep learning. Machine learning provides us an incredible set of tools. If there is a difficult problem in hand, we need not find an algorithm for it, it finds out by itself what is important about the problem and tries to solve it on its own. In many ...
Research talk: Making deep reinforcement learning industrially applicableDeep reinforcement learning has achieved remarkable success, especially in gaming and other applications whose environments are artificial or are associated with low exploration costs. However, for most critical industrial application...
“Deep Learning Techniques for Automation and Industrial Applications” presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, ...
Deep learning (DL) is a very powerful computational tool for various applications in scientific and industrial research which can be real-time implemented for societal benefits. Several factors impact the development of optimized DL models for better prediction including the amount of quality sample dat...
这本书名为《Deep Reinforcement Learning and Its Industrial Use Cases: AI for Real-World Applications》,由Shubham Mahajan、Pethuru Raj和Amit Kant Pandit编辑,出版于2024年。书中探讨了深度强化学习(Deep Reinforcement Learning, DRL)在各个工业领域中的应用,以及如何在现实世界的场景中解决复杂的决策问题。以下...
Deep Learning for Financial Applications : A Survey 摘要 在过去的几十年中,金融领域的计算智能一直是学术界和金融业非常普遍的话题。 已经发表了许多研究,得出了各种模型。 同时,在机器学习(ML)领域中,深度学习(DL)最近开始受到广泛关注,这主要是由于其优于经典模型的表现。 如今,存在许多不同的DL实现,并且人们...
Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large...
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署) - PaddlePaddle/Paddle
Bertolinia M, Mezzogorib D, Neronib M, Zammorib F (2021) Machine Learning for industrial applications: a comprehensive literature review. Expert Syst Appl 175:114820 Article Google Scholar Biggs EM, Bruce E, Boruff B, Duncan JM, Horsley J, Pauli N, Imanari Y (2015) Sustainable development...