Results 81 to 90 of about 9,534,538 (365)
Accelerating Deep Learning with Shrinkage and Recall
, 2016 Deep Learning is a very powerful machine learning model. Deep Learning trains a large number of parameters for multiple layers and is very slow when data is in large scale and the architecture size is large.
Ding, Chris +2 more
core +1 more source
An Introduction to Deep Learning for the Physical Layer [PDF]
IEEE Transactions on Cognitive Communications and Networking, 2017 We present and discuss several novel applications of deep learning for the physical layer. By interpreting a communications system as an autoencoder, we develop a fundamental new way to think about communications system design as an end-to-end ...
Tim O'Shea, J. Hoydis
semanticscholar +1 more source
Deep learning? What deep learning?
South African Journal of Higher Education, 2003 In teaching generally over the past twenty years, there has been a move towards teaching methods that encourage deep, rather than surface approaches to learning. The reason for this being that students, who adopt a deep approach to learning are considered to have learning outcomes of a better quality and desirability than those who adopt a surface ...
openaire +3 more sources
Quantum Information and Computation, 2016 In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on conventional, classical computers.
Ashish Kapoor +2 more
openaire +3 more sources
Book review of “Here, there, everywhere—A memoir” by Peter Almond
, 2022 Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022.
Bruce J. Gerbi
wiley +1 more source
BiomimeticsIn recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring.
Mingen Wang +6 more
doaj +1 more source
Quantum Neural Networks: Concepts, Applications, and Challenges [PDF]
arXiv, 2021 Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks. The research topics and directions of deep learning and quantum computing have been separated for long time, however by discovering that quantum circuits can act like artificial neural networks, quantum deep learning research is ...
arxiv
, 2017 Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing - data ...
Aimone, James B. +8 more
core +1 more source
Deep Learning in Neuroradiology [PDF]
American Journal of Neuroradiology, 2018 Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to medical imaging.
G. Zaharchuk +4 more
openaire +3 more sources
FEBS Letters, EarlyView.This study explores the distinct molecular mechanisms underlying Lynch syndrome‐associated and sporadic colorectal cancer (CRC). By highlighting the therapeutic potential of targeting the PI3K‐Akt pathway in Lynch syndrome‐associated CRC and the Wnt pathway in sporadic CRC, the findings open avenues for personalised treatment strategies, aiming to ...
May J. Krause +2 more
wiley +1 more source