Results 71 to 80 of about 2,291,078 (312)
Multi-Class Adaptive Active Learning for Predicting Student Anxiety
IEEE AccessThis research delves into applying active and machine learning techniques to predict student anxiety. This research explores how these technologies can be explored to understand and predict student anxiety levels.
Ahmad Almadhor +6 more
doaj +1 more source
Deep active learning for classifying cancer pathology reports
BMC Bioinformatics, 2021 Background Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive.
Kevin De Angeli +11 more
doaj +1 more source
Life, 2022 This study was a multicenter retrospective cohort study of term nulliparous women who underwent labor, and was conducted to develop an automated machine learning model for prediction of emergent cesarean section (CS) before onset of labor.
Jeong Ha Wie +15 more
doaj +1 more source
A Machine Learning Based Analytical Framework for Semantic Annotation Requirements
, 2011 The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable ...
Hassanzadeh, Hamed +1 more
core +1 more source
Machine learning phases of active matter
, 2022 5 pages, 4 ...
Xue, Tingting +4 more
openaire +2 more sources
Probe microscopy is all you need
Machine Learning: Science and Technology, 2023 We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods.
Sergei V Kalinin +5 more
doaj +1 more source
A novel activity pattern generation incorporating deep learning for transport demand models [PDF]
arXiv, 2021 Activity generation plays an important role in activity-based demand modelling systems. While machine learning, especially deep learning, has been increasingly used for mode choice and traffic flow prediction, much less research exploiting the advantage of deep learning for activity generation tasks.
arxiv
Human-Like Active Learning: Machines Simulating the Human Learning Process [PDF]
arXiv, 2020 Although the use of active learning to increase learners' engagement has recently been introduced in a variety of methods, empirical experiments are lacking. In this study, we attempted to align two experiments in order to (1) make a hypothesis for machine and (2) empirically confirm the effect of active learning on learning.
arxiv
Enhancing Voice Authentication with a Hybrid Deep Learning and Active Learning Approach for Deepfake Detection [PDF]
This paper explores the application of active learning to enhance machine learning classifiers for spoofing detection in automatic speaker verification (ASV) systems.
Ahmed, Ali Saadoon, Khaleel, Arshad M.
core +2 more sources
Characterizing Uncertainty in Machine Learning for Chemistry
Journal of Chemical Information and Modeling, 2023 Characterizing uncertainty in machine learning models has recently gained interest in the context of machine learning reliability, robustness, safety, and active learning. Here, we separate the total uncertainty into contributions from noise in the data (
Esther Heid +3 more
semanticscholar +1 more source