Results 41 to 50 of about 16,800,197 (383)

Effect of different noise reduction techniques and template matching parameters on markerless tumor tracking using dual‐energy imaging

open access: yesJournal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022
Abstract Purpose To evaluate the impact of various noise reduction algorithms and template matching parameters on the accuracy of markerless tumor tracking (MTT) using dual‐energy (DE) imaging. Methods A Varian TrueBeam linear accelerator was used to acquire a series of alternating 60 and 120 kVp images (over a 180° arc) using fast kV switching, on ...
Mandeep Kaur   +9 more
wiley   +1 more source

Learning for a Robot: Deep Reinforcement Learning, Imitation Learning, Transfer Learning [PDF]

open access: yesSensors, 2021
Dexterous manipulation of the robot is an important part of realizing intelligence, but manipulators can only perform simple tasks such as sorting and packing in a structured environment. In view of the existing problem, this paper presents a state-of-the-art survey on an intelligent robot with the capability of autonomous deciding and learning.
Jiang Hua   +3 more
openaire   +5 more sources

Sparse online relative similarity learning [PDF]

open access: yes, 2021
For many data mining and machine learning tasks, the quality of a similarity measure is the key for their performance. To automatically find a good similarity measure from datasets, metric learning and similarity learning are proposed and studied extensively. Metric learning will learn a Mahalanobis distance based on positive semi-definite (PSD) matrix,
arxiv   +1 more source

Transfer and Learning to Learn in Perceptual Learning [PDF]

open access: yesi-Perception, 2011
As there is considerable current interest in the training characteristics that produce nonspecific perceptual learning, we propose that it may be useful to differentiate between “transfer” and “learning to learn.” These two constructs emerge from learning at different levels of a hierarchical Bayesian model.
openaire   +3 more sources

Guidelines for Quality Assurance and Accreditation of MOOCs [PDF]

open access: yes, 2016
Massive open online courses (MOOCs) have emerged as an educational innovation with the potential to increase access to and improve the quality of education. Different stakeholders in education view MOOCs from different perspectives.
Commonwealth of Learning,   +1 more
core   +3 more sources

From Knowing to Doing: Learning Diverse Motor Skills through Instruction Learning [PDF]

open access: yesarXiv, 2023
Recent years have witnessed many successful trials in the robot learning field. For contact-rich robotic tasks, it is challenging to learn coordinated motor skills by reinforcement learning. Imitation learning solves this problem by using a mimic reward to encourage the robot to track a given reference trajectory.
arxiv  

Smart learning futures: a report from the 3rd US-China smart education conference

open access: yesSmart Learning Environments, 2018
The third day of the third US-China Smart Education Conference featured a discussion with 27 thinkers representing higher education, business and industry, vocational training, and policy making.
J. Michael Spector   +1 more
doaj   +1 more source

The power of microRNA regulation—insights into immunity and metabolism

open access: yesFEBS Letters, EarlyView.
MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto   +2 more
wiley   +1 more source

Some Insights into Lifelong Reinforcement Learning Systems [PDF]

open access: yesarXiv, 2020
A lifelong reinforcement learning system is a learning system that has the ability to learn through trail-and-error interaction with the environment over its lifetime. In this paper, I give some arguments to show that the traditional reinforcement learning paradigm fails to model this type of learning system.
arxiv  

Flow‐based immunomagnetic enrichment of circulating tumor cells from diagnostic leukapheresis product

open access: yesMolecular Oncology, EarlyView.
The number of circulating tumor cells obtained from prostate cancer patients was increased approximately 5‐fold compared to regular CellSearch when processing 2 mL diagnostic leukapheresis material aliquots and increased by 44‐fold when processing 20 mL DLA aliquots using the flow enrichment target capture Halbach‐array.
Michiel Stevens   +8 more
wiley   +1 more source

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