Backbones-review: Feature extraction networks for deep learning and deep reinforcement learning approaches

O Elharrouss, Y Akbari, N Almaadeed… - arXiv preprint arXiv …, 2022 - arxiv.org
To understand the real world using various types of data, Artificial Intelligence (AI) is the
most used technique nowadays. While finding the pattern within the analyzed data …

The history began from alexnet: A comprehensive survey on deep learning approaches

MZ Alom, TM Taha, C Yakopcic, S Westberg… - arXiv preprint arXiv …, 2018 - arxiv.org
Deep learning has demonstrated tremendous success in variety of application domains in
the past few years. This new field of machine learning has been growing rapidly and applied …

[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures

MZ Alom, TM Taha, C Yakopcic, S Westberg, P Sidike… - electronics, 2019 - mdpi.com
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …

Review of deep learning algorithms and architectures

A Shrestha, A Mahmood - IEEE access, 2019 - ieeexplore.ieee.org
Deep learning (DL) is playing an increasingly important role in our lives. It has already made
a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars …

Deep learning: a comprehensive overview on techniques, taxonomy, applications and research directions

IH Sarker - SN computer science, 2021 - Springer
Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is
nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or …

[PDF][PDF] Model-driven deep-learning

Z Xu, J Sun - National Science Review, 2018 - academic.oup.com
Deep learning has been widely recognized as the representative advances of machine
learning or artificial intelligence in general nowadays [1, 2]. This can be attributed to the …

Training larger networks for deep reinforcement learning

K Ota, DK Jha, A Kanezaki - arXiv preprint arXiv:2102.07920, 2021 - arxiv.org
The success of deep learning in the computer vision and natural language processing
communities can be attributed to training of very deep neural networks with millions or …

Deep reinforcement learning: an overview

SS Mousavi, M Schukat, E Howley - Proceedings of SAI Intelligent Systems …, 2018 - Springer
In recent years, a specific machine learning method called deep learning has gained huge
attraction, as it has obtained astonishing results in broad applications such as pattern …

[图书][B] Deep Reinforcement Learning

H Dong, H Dong, Z Ding, S Zhang, T Chang - 2020 - Springer
Deep reinforcement learning (DRL) combines deep learning (DL) with a reinforcement
learning (RL) architecture. It has been able to perform a wide range of complex decision …

Modern deep reinforcement learning algorithms

S Ivanov, A D'yakonov - arXiv preprint arXiv:1906.10025, 2019 - arxiv.org
Recent advances in Reinforcement Learning, grounded on combining classical theoretical
results with Deep Learning paradigm, led to breakthroughs in many artificial intelligence …